Methods for operating a radio wave based health monitoring system that involve determining an alignment

ABSTRACT

A method for operating a health parameter monitoring system is disclosed. The method involves transmitting radio waves below the skin surface of a person, receiving radio waves on a two-dimensional array of receive antennas of an antenna array, the received radio waves including a reflected portion of the transmitted radio waves, determining an alignment of the antenna array relative to a vein in the person in response to the received radio waves, and outputting a signal that is indicative of the determined alignment of the antenna array relative to the vein.

BACKGROUND

Diabetes is a medical disorder in which a person's blood glucose level,also known as blood sugar level, is elevated over an extended period oftime. If left untreated, diabetes can lead to severe medicalcomplications such as cardiovascular disease, kidney disease, stroke,foot ulcers, and eye damage. It has been estimated that the total costof diabetes in the U.S. in 2017 was $327 billion, American DiabetesAssociation, “Economic Costs of Diabetes in the U.S. in 2017,” publishedonline on Mar. 22, 2018.

Diabetes is typically caused by either the pancreas not producing enoughinsulin, referred to as “Type 1” diabetes, or because the cells of theperson do not properly respond to insulin that is produced, referred toas “Type 2” diabetes. Managing diabetes may involve monitoring aperson's blood glucose level and administering insulin when the person'sblood glucose level is too high to bring the blood glucose level down toa desired level. A person may need to measure their blood glucose levelup to ten times a day depending on many factors, including the severityof the diabetes and the person's medical history. Billions of dollarsare spent each year on equipment and supplies used to monitor bloodglucose levels.

SUMMARY

A method for operating a health parameter monitoring system isdisclosed. The method involves transmitting radio waves below the skinsurface of a person, receiving radio waves on a two-dimensional array ofreceive antennas of an antenna array, the received radio waves includinga reflected portion of the transmitted radio waves, determining analignment of the antenna array relative to a vein in the person inresponse to the received radio waves, and outputting a signal that isindicative of the determined alignment of the antenna array relative tothe vein.

Other aspects in accordance with the invention will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, illustrated by way of example of the principlesof the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are perspective views of a smartwatch.

FIG. 2A depicts a posterior view of a right hand with the typicalapproximate location of the cephalic vein and the basilic veinoverlaid/superimposed.

FIG. 2B depicts the location of a cross-section of the wrist from FIG.2A.

FIG. 2C depicts the cross-section of the wrist from the approximatelocation shown in FIG. 2B (as viewed in the direction from the elbow tothe hand).

FIG. 3 is a perspective view of human skin that includes a skin surface,hairs, and the epidermis and dermis layers of the skin.

FIG. 4A depicts a simplified version of the cross-section of FIG. 2C,which shows the skin, the radius and ulna bones, and the basilic vein.

FIG. 4B depicts the wrist cross-section of FIG. 4A in a case where asmartwatch is attached to the wrist.

FIG. 4C illustrates, in two dimensions, an example of the penetrationdepth (which corresponds to a 3D illumination space) of radio wavestransmitted from the sensor system of the smartwatch at a frequency of60 GHz and a transmission power of 15 dBm.

FIG. 4D illustrates, in two dimensions, an example of the penetrationdepth (which corresponds to a 3D illumination space) of radio wavestransmitted from the sensor system of the smartwatch at a frequency of122-126 GHz and transmit power of 15 dBm.

FIG. 5 depicts a functional block diagram of an embodiment of a sensorsystem that utilizes millimeter range radio waves to monitor a healthparameter such as the blood glucose level in a person.

FIG. 6 depicts an expanded view of an embodiment of portions of thesensor system of FIG. 5, including elements of the RF front-end.

FIG. 7 depicts an embodiment of the IF/BB component shown in FIG. 6.

FIG. 8A depicts an example embodiment of a plan view of an IC devicethat includes two TX antennas and four antennas 846 as well as some ofthe components from the RF front-end and the digital baseband (notshown) as described above with regard to FIGS. 5-7.

FIG. 8B depicts an embodiment of a microstrip patch antenna that can beused for the TX and/or RX antennas of the IC device of FIG. 8A.

FIG. 8C depicts an example of the physical layout of circuit componentson a semiconductor substrate, such as the semiconductor substrate (die)depicted in FIG. 8A.

FIG. 8D depicts a packaged IC device similar to the packaged IC deviceshown in FIG. 8A superimposed over the semiconductor substrate shown inFIG. 8C.

FIG. 9 depicts an IC device similar to that of FIG. 8A overlaid on thehand/wrist that is described above with reference to FIG. 2A-2C.

FIG. 10 depicts an IC device similar to that of FIG. 8A overlaid on theback of the smartwatch.

FIG. 11 depicts a side view of a sensor system in a case in which thetwo TX antennas are configured parallel to veins such as the basilic andcephalic veins of a person wearing the smartwatch.

FIG. 12 depicts the same side view as shown in FIG. 11 in a case inwhich the two TX antennas are configured transverse to veins such as thebasilic and cephalic veins of a person wearing the smartwatch.

FIGS. 13A-13C depict frequency versus time graphs of impulse, chirp, andstepped frequency techniques for transmitting electromagnetic energy ina radar system.

FIG. 14 depicts a burst of electromagnetic energy using steppedfrequency transmission.

FIG. 15A depicts a graph of the transmission bandwidth, B, oftransmitted electromagnetic energy in the frequency range of 122-126GHz.

FIG. 15B depicts a graph of stepped frequency pulses that have arepetition interval, T, and a step size, Δf, of 62.5 MHz.

FIG. 16A depicts a frequency versus time graph of transmission pulses,with transmit (TX) interval and receive (RX) intervals identifiedrelative to the pulses.

FIG. 16B depicts an amplitude versus time graph of the transmissionwaveforms that corresponds to FIG. 16A.

FIG. 17 illustrates operations related to transmitting, receiving, andprocessing phases of the sensor system operation.

FIG. 18 depicts an expanded view of the anatomy of a wrist, similar tothat described above with reference to FIGS. 2A-4D, relative to RXantennas of a sensor system that is integrated into a wearable devicesuch as a smartwatch.

FIG. 19 illustrates an IC device similar to the IC device shown in FIG.8A relative to a vein and blood flowing through the vein.

FIG. 20 is an embodiment of a DSP that includes a Doppler effectcomponent, a beamforming component, and a ranging component.

FIG. 21 is a process flow diagram of a method for monitoring a healthparameter in a person.

FIG. 22A depicts a side view of the area around a person's ear with thetypical approximate locations of veins and arteries, including thesuperficial temporal artery, the superficial temporal vein, the anteriorauricular artery and vein, the posterior auricular artery, the occipitalartery, the external carotid artery, and the external jugular vein.

FIG. 22B depicts an embodiment of system in which at least elements ofan RF front-end are located separate from a housing.

FIG. 22C illustrates how a device, such as the device depicted in FIG.22B, may be worn near the ear of a person similar to how a conventionalhearing aid is worn.

FIG. 23 is a table of parameters related to stepped frequency scanningin a system such as the above-described system.

FIG. 24 is a table of parameters similar to the table of FIG. 23 inwhich examples are associated with each parameter for a given step in astepped frequency scanning operation in order to give some context tothe table.

FIG. 25 depicts an embodiment of the IC device from FIG. 8A in which theantenna polarization orientation is illustrated by the orientation ofthe transmit and receive antennas.

FIG. 26 is a table of raw data that is generated during steppedfrequency scanning.

FIG. 27 illustrates a system and process for machine learning that canbe used to identify and train a model that reflects correlations betweenraw data, derived data, and control data.

FIG. 28 is an example of a process flow diagram of a method forimplementing machine learning.

FIG. 29 is an example of a table of a raw data record generated duringstepped frequency scanning that is used to generate the training data.

FIGS. 30A-30D are tables of at least portions of raw data records thatare generated during a learning process that spans the time of t1-tn,where n corresponds to the number of time intervals, T, in the steppedfrequency scanning.

FIG. 31 illustrates a system for health parameter monitoring thatutilizes a sensor system similar to or the same as the sensor systemdescribed with reference to FIGS. 5-7.

FIG. 32 is a process flow diagram of a method for monitoring a healthparameter in a person.

FIG. 33 is a process flow diagram of another method for monitoring ahealth parameter in a person.

FIG. 34 is a process flow diagram of a method for training a model foruse in monitoring a health parameter in a person.

FIGS. 35A-35E illustrate the antennas of the sensor system as describedabove with reference to FIGS. 5-8D and a vein aligned between the TX andRX antennas of the sensor system.

FIGS. 36A-36E illustrate an example of RF-based alignment of a sensorsystem to a vein on a graphical user interface of a smartwatch.

FIGS. 37A and 37B illustrate an example of the alignment processdescribed with reference to FIGS. 36A-36E.

FIG. 37C illustrates an alignment indicator on a graphical userinterface of a smartwatch relative to the actual location of a vein inthe arm of a person.

FIGS. 38A and 38B illustrate another example of an alignment process.

FIGS. 39A and 39B depict an example of another type of RF-basedalignment feature that can be used to align an antenna array of a sensorsystem with a monitored vein.

FIGS. 40A and 40B depict an embodiment of a smartphone that includes asensor system integrated into the smartphone.

FIGS. 41A and 41B depict an embodiment of a smartphone that includes asensor system with multiple RF front-ends integrated into thesmartphone.

FIGS. 42A and 42B depict an embodiment of a smartphone that includes asensor system as described with reference to FIGS. 5-8D that isconfigured to implement RF-based alignment of an antenna array of thesensor system to a vein of a person that is to be monitored.

FIG. 43A depicts an example of the veins in the arm of a person.

FIG. 43B depicts a smartphone, such as the smartphone described withreference to FIGS. 41A-42B placed on the skin at the location of (or inclose proximity to) a vein such as the intermediate vein of the forearm.

FIGS. 44A and 44B depict the backside and frontside of a smartphone inwhich a sensor system including the antenna array is located at a pointnear the bottom of the smartphone.

FIG. 44C illustrates a person holding the smartphone as described withreference to FIGS. 44A and 44B against the skin at the wrist and usingthe alignment feature on the graphical user interface to align thesensor system of the smartphone with the monitored vein.

FIG. 45A depicts the backside of a smartphone in which the sensor systemis located at a point near the bottom of the smartphone, similar to theexample described with reference to FIG. 44A.

FIG. 45B depicts the frontside of the smartphone from FIG. 45A in whichan alignment feature is provided as a marking on the body of thesmartphone that is visible to a user of the smartphone.

FIG. 46 is a perspective view of a removable smartphone case.

FIGS. 47A and 47B depict the backside and frontside, respectively, of anembodiment of a removable smartphone case that includes a sensor systemhaving an RF front-end, a processor, a communications interface, and abattery integrated into the case.

FIG. 47C depicts a side cutaway view of the removable smartphone caseshown at cross section AA of FIG. 47A.

FIGS. 48A and 48B depict the frontside and backside, respectively, of anembodiment of a removable smartphone case that includes a sensor systemin which the antenna array of the RF front-end is separated from thesemiconductor substrate of the front RF front-end.

FIG. 49A depicts the backside of a removable smartphone case in whichthe sensor system is integrated into the case and the communicationsinterface is a wired interface such as a male interface that isconfigured to connect to a female interface of a smartphone.

FIG. 49B depicts a perspective view of the removable smartphone case ofFIG. 49A.

FIG. 50A illustrates alignment information being communicated from theremovable smartphone case to the smartphone.

FIG. 50B illustrates health parameter information being communicatedfrom the removable smartphone case to the smartphone.

FIGS. 51A-51C depict an embodiment of a smartphone that includesmagnetic alignment features integrated into the body of the smartphone.

FIGS. 52A-52C depict an embodiment of a removable smartphone case thatincludes magnetic alignment elements integrated into the body of theremovable smartphone case.

FIGS. 53A and 53B depict an embodiment of an alignment element in theform of an alignment patch that includes magnetic alignment featuresconfigured to mate with alignment features of the health monitoringdevice.

FIGS. 54A-54C illustrate an example alignment process between a healthmonitoring device and an alignment element in which the healthmonitoring device and the alignment element include matchingconfigurations of magnetic alignment features.

FIGS. 55A and 55B depict an example of a removable smartphone case inwhich the antenna array of the sensor system is not collocated with thealignment features.

FIGS. 56A-56C depict an embodiment of a smartphone with out-of-planephysical elements that are integrated into the device body andconfigured to promote alignment between an antenna array of a sensorsystem and an object such as an alignment patch.

FIGS. 57A-57C depict an embodiment of the removable smartphone case thatincludes out-of-plane alignment elements integrated into the body of theremovable smartphone case.

FIGS. 58A and 58B depict an embodiment of an alignment patch thatincludes out-of-plane alignment features configured to mate without-of-plane alignment features of the health monitoring device.

FIGS. 59A-59C illustrate an example alignment process between a healthmonitoring device and an alignment element in which the healthmonitoring device and the alignment element include matching orcomplimentary configurations of out-of-plane alignment features.

FIGS. 60A and 60B depict perspective views of a health monitoring devicein the form of a smartwatch in which alignment features such as magneticalignment elements are integrated into the backside of the smartwatchbody.

FIG. 60C is a side cutaway view of the smartwatch from FIGS. 60A and 60Battached around a wrist with the magnetic alignment features of thesmartwatch magnetically engaged with complementary magnetic alignmentfeatures of an alignment patch that is attached to the skin of thewrist.

FIGS. 61A and 61B depict perspective views of a health monitoring devicein the form of a smartwatch in which out-of-plane alignment features areintegrated into the backside of the smartwatch body.

FIG. 61C is a side cutaway view of the smartwatch from FIG. 61B attachedaround a wrist with the out-of-plane alignment features of thesmartwatch seated on top of complementary out-of-plane alignmentfeatures of an alignment patch that is attached to the skin of thewrist.

FIGS. 62A and 62B depict an embodiment in which an RF-based healthmonitoring system is integrated into a watch strap.

FIGS. 63A-63F depict an example of wearable health monitoring systemthat includes a health monitoring device and an alignment element, suchas an alignment patch.

FIGS. 64A-64C depict an embodiment in which an RF-based healthmonitoring system is integrated into a ring that is to be worn on afinger or toe.

FIG. 65 is an example computing system that includes an RF-based sensorsystem, a processor, memory, a communications interface, a battery, adisplay device, a tactile indicator device, and a speaker.

Throughout the description, similar reference numbers may be used toidentify similar elements.

DETAILED DESCRIPTION

It will be readily understood that the components of the embodiments asgenerally described herein and illustrated in the appended figures couldbe arranged and designed in a wide variety of different configurations.Thus, the following more detailed description of various embodiments, asrepresented in the figures, is not intended to limit the scope of thepresent disclosure, but is merely representative of various embodiments.While the various aspects of the embodiments are presented in drawings,the drawings are not necessarily drawn to scale unless specificallyindicated.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by this detailed description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

Reference throughout this specification to features, advantages, orsimilar language does not imply that all of the features and advantagesthat may be realized with the present invention should be or are in anysingle embodiment of the invention. Rather, language referring to thefeatures and advantages is understood to mean that a specific feature,advantage, or characteristic described in connection with an embodimentis included in at least one embodiment of the present invention. Thus,discussions of the features and advantages, and similar language,throughout this specification may, but do not necessarily, refer to thesame embodiment.

Furthermore, the described features, advantages, and characteristics ofthe invention may be combined in any suitable manner in one or moreembodiments. One skilled in the relevant art will recognize, in light ofthe description herein, that the invention can be practiced without oneor more of the specific features or advantages of a particularembodiment. In other instances, additional features and advantages maybe recognized in certain embodiments that may not be present in allembodiments of the invention.

Reference throughout this specification to “one embodiment”, “anembodiment”, or similar language means that a particular feature,structure, or characteristic described in connection with the indicatedembodiment is included in at least one embodiment of the presentinvention. Thus, the phrases “in one embodiment”, “in an embodiment”,and similar language throughout this specification may, but do notnecessarily, all refer to the same embodiment.

Traditional blood glucose level monitoring is accomplished by pricking afinger to draw blood and measuring the blood glucose level with a bloodglucose meter, or “glucometer.” Continuous glucose monitoring can beaccomplished by applying a continuous glucose monitor (CGM) to an areaon the body such as the torso. The continuous glucose monitor utilizes aneedle that is continuously embedded through the skin to obtain accessto blood. Although blood glucose meters and continuous glucose monitorswork well to monitor blood glucose levels, both techniques are invasivein nature in that they require physical penetration of the skin by asharp object.

Various non-invasive techniques for monitoring blood glucose levels havebeen explored. Example techniques for monitoring blood glucose levelsinclude techniques based on infrared (IR) spectroscopy, near infrared(NIR) spectroscopy, mid infrared (MIR) spectroscopy, photoacousticspectroscopy, fluorescence spectroscopy, Raman spectroscopy, opticalcoherence tomography (OCT), and microwave sensing, Ruochong Zhang etal., “Noninvasive Electromagnetic Wave Sensing of Glucose,” Oct. 1,2018.

In the category of microwave sensing, millimeter range radio waves havebeen identified as useful for monitoring blood glucose levels. Anexample of using millimeter range radio waves to monitor blood glucoselevels is described by Peter H. Siegel et al., “Millimeter-WaveNon-Invasive Monitoring of Glucose in Anesthetized Rats,” 2014International Conference on Infrared, Millimeter, and Terahertz Waves,Tucson, Ariz., Sep. 14-19, 2014. Here, Siegel et al. describes using theKa band (27-40 GHz) to measure blood glucose levels through the ear of alab rat.

Another example of using millimeter range radio waves to monitor bloodglucose levels is described by George Shaker et al., “Non-InvasiveMonitoring of Glucose Level Changes Utilizing a mm-Wave Radar System,”International Journal of Mobile Human Computer Interaction, Volume 10,Issue 3, July-September 2018. Here, Shaker et al. utilizes a millimeterrange sensing system referred to as “Soli,” (see Jaime Lien et. al.,“Soli: Ubiquitous Gesture Sensing with Millimeter Wave Radar,” ACMTrans. Graph. 35, 4 Article 142, July 2016) to monitor blood glucoselevels. Shaker et al. utilizes radio waves in the 57-64 GHz frequencyrange to monitor blood glucose levels. Although the Soli sensor systemincludes transmit (TX) and receive (RX) antennas on the same integratedcircuit (IC) device (i.e., the same “chip”) and thus in the same plane,Shaker et al. concludes that for blood glucose monitoring, a radarsensing system configuration would ideally have its antennas placed onopposite sides of the sample under test to be able to effectivelymonitor blood glucose levels. When the transmit (TX) and receive (RX)antennas were on the same side of the sample under test, Shaker et al.was not able to find any discernible trend in the magnitude or phase ofthe sensor signals.

Another example of using millimeter range radio waves to monitor bloodglucose levels is described by Shimul Saha et al., “A Glucose SensingSystem Based on Transmission Measurements at Millimeter Waves usingMicro strip Patch Antennas,” Scientific Reports, published online Jul.31, 2017. Here, Saha et al. notes that millimeter wave spectroscopy inreflection mode has been used for non-invasive glucose sensing throughhuman skin, but concludes that signals from reflection mode detectionyield information that is insufficient for tracking the relevant changesin blood glucose levels. Saha et al. investigates radio waves in therange of 20-100 GHz for monitoring blood glucose levels and concludesthat an optimal sensing frequency is in the range of 40-80 GHz.

Although blood glucose level monitoring using millimeter range radiowaves has been shown to be technically feasible, implementation ofpractical monitoring methods and systems has yet to be realized. Forexample, a practical realization of a monitoring system may include amonitoring system that can be integrated into a wearable device, such asa smartwatch.

In accordance with an embodiment of the invention, methods and systemsfor monitoring the blood glucose level of a person using millimeterrange radio waves involve transmitting millimeter range radio wavesbelow the skin surface, receiving a reflected portion of the radio waveson multiple receive antennas, isolating a signal from a particularlocation in response to the received radio waves, and outputting asignal that corresponds to a blood glucose level in the person inresponse to the isolated signals. In an embodiment, beamforming is usedin the receive process to isolate radio waves that are reflected from aspecific location (e.g., onto a specific blood vessel) to provide ahigh-quality signal that corresponds to blood glucose levels in thespecific blood vessel. In another embodiment, Doppler effect processingcan be used to isolate radio waves that are reflected from a specificlocation (e.g., reflected from a specific blood vessel) to provide ahigh-quality signal that corresponds to blood glucose levels in thespecific blood vessel. Analog and/or digital signal processingtechniques can be used to implement beamforming and/or Doppler effectprocessing and digital signal processing of the received signals can beused to dynamically adjust (or “focus”) a received beam onto the desiredlocation. In still another embodiment, beamforming and Doppler effectprocessing can be used together to isolate radio waves that arereflected from a specific location (e.g., reflected from a specificblood vessel) to provide a high-quality signal that corresponds to bloodglucose levels in the specific blood vessel.

As described above, Siegal et al., Shaker et al., and Saha et al.,utilize radio waves in the range of about 27-80 GHz, commonly around 60GHz, to monitor blood glucose levels. Saha et al. discloses that afrequency of around 60 GHz is desirable for glucose detection usingelectromagnetic transmission data and notes that for increasingly higherfrequencies, the losses are prohibitively high for the signal-to-noiseratio (SNR) to exceed the noise level of a sensing instrument such as aVector Network Analyzer (VNA).

In contrast to conventional techniques, it has been discovered thatusing a higher frequency range, e.g., 122-126 GHz, to monitor bloodglucose levels can provide certain benefits that heretofore have notbeen recognized. For example, transmitting millimeter range radio wavesin the frequency range of 122-126 GHz results in a shallower penetrationdepth within a human body than radio waves in the frequency range around60 GHz for a similar transmission power. A shallower penetration depthcan reduce undesirable reflections (e.g., reflections off of bone anddense tissue such as tendons, ligaments, and muscle), which can reducethe signal processing burden and improve the quality of the desiredsignal that is generated from the location of a blood vessel.

Additionally, transmitting millimeter range radio waves in the frequencyrange of 122-126 GHz enables higher resolution sensing than radio wavesat around 60 GHz due to the shorter wavelengths, e.g., 2.46-2.38 mm for122-126 GHz radio waves versus 5 mm for 60 GHz radio waves. Higherresolution sensing allows a receive beam to be focused more precisely(e.g., through beamforming and/or Doppler effect processing) onto aparticular blood vessel, such as the basilic vein on the posterior ofthe wrist, which can also improve the quality of the desired signal.

Additionally, utilizing millimeter range radio waves in the frequencyrange of 122-126 GHz to monitor blood glucose levels enables the size ofthe corresponding transmit and receive antennas to be reduced incomparison to techniques that utilize radio waves in the frequency rangeof 20-80 GHz. For example, the size of antennas can be reduced by afactor of approximately two by using radio waves in the 122-126 GHzfrequency range instead of radio waves in the 60 GHz frequency range,which can enable a smaller form factor for the antennas and for theoverall sensor system. Additionally, the frequency range of 122-126 GHzis an unlicensed band of the industrial, scientific, and medical (ISM)radio bands as defined by the International Telecommunication Union(ITU) Radio Regulations. Thus, methods and systems for monitoring bloodglucose levels that are implemented using a frequency range of 122-126GHz do not require a license.

FIGS. 1A and 1B are perspective views of a smartwatch 100, which is adevice that provides various computing functionality beyond simplygiving the time. Smartwatches are well known in the field. Thesmartwatch includes a case 102 (also referred to as a “housing”) and astrap 104 (e.g., an attachment device) and the strap is typicallyattached to the case by lugs (not shown). FIG. 1A is a top perspectiveview of the smartwatch that shows a front face 106 of the case and acrown 108 and FIG. 1B is a back perspective view of the smartwatch thatshows a back plate of the case. FIG. 1B also includes a dashed lineblock 110 that represents a sensor system, such as a sensor system forhealth monitoring. The sensor system may be partially or fully embeddedwithin the case. In some embodiments, the sensor system may include asensor integrated circuit (IC) device or IC devices with transmit and/orreceive antennas integrated therewith. In some embodiments, the backplate of the case may have openings that allow radio waves to pass moreeasily to and from smartwatch. In some embodiments, the back plate ofthe case may have areas of differing materials that create channelsthrough which radio waves can pass more easily. For example, in anembodiment, the back plate of the case may be made primarily of metalwith openings in the metal at locations that correspond to sensorantennas that are filled with a material (e.g., plastic or glass) thatallows radio waves to pass to and from the smartwatch more easily thanthrough the metal case.

Although a smartwatch is described as one device in which a millimeterrange radio wave sensing system can be included, a millimeter rangeradio wave sensing system can be included in other sensing devices,including various types of wearable devices and/or devices that are notwearable but that are brought close to, or in contact with, the skin ofa person only when health monitoring is desired. For example, amillimeter range radio wave sensing system can be incorporated into asmartphone. In an embodiment, a millimeter range radio wave sensingsystem can be included in a health and fitness tracking device that isworn on the wrist and tracks, among other things, a person's movements.In another embodiment, a millimeter range radio wave sensing system canbe incorporated into a device such as dongle or cover (e.g., aprotective cover that is placed over a smartphone for protection) thatis paired (e.g., via a local data connection such as USB or BLUETOOTH)with a device such as a smartphone or smartwatch to implement healthmonitoring. For example, a dongle may include many of the componentsdescribed below with reference to FIG. 6, while the paired device (e.g.,the smartphone or smartwatch) includes a digital signal processingcapability (e.g., through a Digital Signal Processor (DSP)) andinstruction processing capability (e.g., through a Central ProcessingUnit (CPU)). In another example, a millimeter range sensing system maybe incorporated into a device that is attached to the ear. In anembodiment, the sensing system could be attached to the lobe of the earor have an attachment element that wraps around the ear or wraps arounda portion of the ear.

Wearable devices such as smartwatches and health and fitness trackersare often worn on the wrist similar to a traditional wristwatch. Inorder to monitor blood glucose levels using millimeter range radiowaves, it has been discovered that the anatomy of the wrist is animportant consideration. FIG. 2A depicts a posterior view of a righthand 212 with the typical approximate location of the cephalic vein 214and the basilic vein 216 overlaid/superimposed. FIG. 2B depicts thelocation of a cross-section of the wrist 218 from FIG. 2A and FIG. 2Cdepicts the cross-section of the wrist 218 from the approximate locationshown in FIG. 2B (as viewed in the direction from the elbow to thehand). In FIG. 2C, the cross-section is oriented on the page such thatthe posterior portion of the wrist is on the top and the anteriorportion of the wrist is on the bottom. The depth dimension of a wrist isidentified on the left side and typically ranges from 40-60 mm (based ona wrist circumference in the range of 140-190 mm). Anatomic features ofthe wrist shown in FIG. 2C include the abductor pollicis longus (APL),the extensor carpi radialis brevis (ECRB), the extensor carpi radialislongus (ECRL), the extensor carpi ulnaris (ECU), the extensor indicisproprius (EIP), the extensor pollicis brevis (EPB), the extensorpollicis longus (EPL), the flexor carpi ulnaris (FCU), the flexordigitorum superficialis (FDS), the flexor pollicis longus (FPL), thebasilic vein 216, the radius, the ulna, the radial artery, the mediannerve, the ulnar artery, and the ulnar nerve. FIG. 2C also depicts theapproximate location of the basilic vein in subcutaneous tissue 220below the skin 222. In some embodiments and as is disclosed below, thelocation of a blood vessel such as the basilic vein is of particularinterest to monitoring blood glucose levels using millimeter range radiowaves.

FIG. 3 is a perspective view of human skin 322 that includes a skinsurface 324, hairs 326, and the epidermis 328 and dermis 330 layers ofthe skin. The skin is located on top of subcutaneous tissue 320. In anexample, the thickness of human skin in the wrist area is around 1-4 mmand the thickness of the subcutaneous tissue may vary from 1-34 mm,although these thicknesses may vary based on many factors. As shown inFIG. 3, very small blood vessels 332 (e.g., capillaries having adiameter in the range of approximately 5-10 microns) are located aroundthe interface between the dermis and the subcutaneous tissue whileveins, such as the cephalic and basilic veins, are located in thesubcutaneous tissue just below the skin. For example, the cephalic andbasilic veins may have a diameter in the range of 1-4 mm and may beapproximately 2-10 mm below the surface of the skin, although thesediameters and depths may vary based on many factors. FIG. 3 depicts anexample location of the basilic vein 316 in the area of the wrist.

FIG. 4A depicts a simplified version of the cross-section of FIG. 2C,which shows the skin 422, the radius and ulna bones 434 and 436, and thebasilic vein 416. FIG. 4B depicts the wrist cross-section of FIG. 4A ina case where a smartwatch 400, such as the smartwatch shown in FIGS. 1Aand 1B, is attached to the wrist. FIG. 4B illustrates an example of thelocation of the smartwatch relative to the wrist and in particularrelative to the basilic vein of the wrist. In the example of FIG. 4B,dashed line block 410 represents the approximate location of a sensorsystem and corresponds to the dashed line block 110 shown in FIG. 1B.The location of the smartwatch relative to the anatomy of the wrist,including the bones and a vein such as the basilic vein, is an importantconsideration in implementing blood glucose monitoring using millimeterrange radio waves.

The magnitude of the reflected and received radio waves is a function ofthe power of the transmitted radio waves. With regard to the anatomy ofthe human body, it has been realized that radio waves transmitted ataround 60 GHz at a particular transmission power level (e.g., 15 dBm)penetrate deeper (and thus illuminate a larger 3D space) into the humanbody than radio waves transmitted at 122-126 GHz at the sametransmission power level (e.g., 15 dBm). FIG. 4C illustrates, in twodimensions, an example of the penetration depth (which corresponds to a3D illumination space) of radio waves 438 transmitted from the sensorsystem of the smartwatch at a frequency of 60 GHz and a transmissionpower of 15 dBm. FIG. 4D illustrates, in two dimensions, an example ofthe penetration depth (which corresponds to a 3D illumination space) ofradio waves 440 transmitted from the sensor system of the smartwatch ata frequency of 122-126 GHz and transmit power of 15 dBm, which is thesame transmission power as used in the example of FIG. 4C. Asillustrated by FIGS. 4C and 4D, for equivalent transmission powers(e.g., 15 dBm), radio waves 438 transmitted at 60 GHz penetrate deeperinto the wrist (and thus have a corresponding larger illumination space)than radio waves 440 that are transmitted at 122-126 GHz. The deeperpenetration depth of the 60 GHz radio waves results in more radio wavesbeing reflected from anatomical features within the wrist. For example,a large quantity of radio waves will be reflected from the radius andulna bones 434 and 436 in the wrist as well as from dense tissue such astendons and ligaments that are located between the skin and the bones atthe posterior of the wrist, see FIG. 2C, which shows tendons andligaments that are located between the skin and the bones at theposterior of the wrist. Likewise the shallower penetration of the122-126 GHz radio waves results in fewer radio waves being reflectedfrom undesired anatomical features within the wrist (e.g., anatomicalfeatures other than the targeted blood vessel or vein). For example, amuch smaller or negligible magnitude of radio waves will be reflectedfrom the radius and ulna bones in the wrist as well as from dense tissuesuch as tendons and ligaments that are located between the skin and thebones at the posterior of the wrist.

It has been realized that the penetration depth (and corresponding 3Dillumination space), is an important factor in the complexity of thesignal processing that is performed to obtain an identifiable signalthat corresponds to the blood glucose level in the wrist (e.g., in thebasilic vein of the wrist). In order to accurately measure the bloodglucose level in a vein such as the basilic vein, it is desirable toisolate reflections from the area of the vein from all of the otherreflections that are detected (e.g., from reflections from the radiusand ulna bones in the wrist as well as from dense tissue such as tendonsand ligaments that are located between the skin and the bones at theposterior of the wrist). In an embodiment, radio waves are transmittedat an initial power such that the power of the radio waves hasdiminished by approximately one-half (e.g., ±10%) at a depth of 6 mmbelow the skin surface. Reflections can be isolated using varioustechniques including signal processing techniques that are used forbeamforming, Doppler effect, and/or leakage mitigation. The largerquantity of reflections in the 60 GHz case will likely need moreintensive signal processing to remove signals that correspond tounwanted reflections in order to obtain a signal of sufficient qualityto monitor a blood parameter such as the blood glucose level in aperson.

FIG. 5 depicts a functional block diagram of an embodiment of a sensorsystem 510 that utilizes millimeter range radio waves to monitor ahealth parameter such as the blood glucose level in a person. The sensorsystem includes transmit (TX) antennas 544, receive (RX) antennas 546,an RF front-end 548, a digital baseband system 550, and a CPU 552. Thecomponents of the sensor system may be integrated together in variousways. For example, some combination of components may be fabricated onthe same semiconductor substrate and/or included in the same packaged ICdevice or a combination of packaged IC devices. As described above, inan embodiment, the sensor system is designed to transmit and receiveradio waves in the range of 122-126 GHz.

In the embodiment of FIG. 5, the sensor system 510 includes two TXantennas 544 and four RX antennas 546. Although two TX and four RXantennas are used, there could be another number of antennas, e.g., oneor more TX antennas and two or more RX antennas. In an embodiment, theantennas are configured to transmit and receive millimeter range radiowaves. For example, the antennas are configured to transmit and receiveradio waves in the 122-126 GHz frequency range, e.g., wavelengths in therange of 2.46-2.38 mm.

In the embodiment of FIG. 5, the RF front-end 548 includes a transmit(TX) component 554, a receive (RX) component 556, a frequencysynthesizer 558, and an analogue processing component 560. The transmitcomponent may include elements such as power amplifiers and mixers. Thereceive component may include elements such as low noise amplifiers(LNAs), variable gain amplifiers (VGAs), and mixers. The frequencysynthesizer includes elements to generate electrical signals atfrequencies that are used by the transmit and receive components. In anembodiment the frequency synthesizer may include elements such as acrystal oscillator, a phase-locked loop (PLL), a frequency doubler,and/or a combination thereof. The analogue processing component mayinclude elements such as mixers and filters, e.g., low pass filters(LPFs). In an embodiment, components of the RF front-end are implementedin hardware as electronic circuits that are fabricated on the samesemiconductor substrate.

The digital baseband system 550 includes an analog-to-digital converter(ADC) 562, a digital signal processor (DSP) 564, and a microcontrollerunit (MCU) 566. Although the digital baseband system is shown asincluding certain elements, the digital baseband system may include someother configuration, including some other combination of elements. Thedigital baseband system is connected to the CPU 552 via a bus.

FIG. 6 depicts an expanded view of an embodiment of portions of thesensor system 510 of FIG. 5, including elements of the RF front-end. Inthe embodiment of FIG. 6, the elements include a crystal oscillator 670,a phase locked loop (PLL) 672, a bandpass filter (BPF) 674, a mixer 676,power amplifiers (PAs) 678, TX antennas 644, a frequency synthesizer680, a frequency doubler 682, a frequency divider 684, a mixer 686, anRX antenna 646, a low noise amplifier (LNA) 688, a mixer 690, a mixer692, and an Intermediate Frequency/Baseband (IF/BB) component 694. Asillustrated in FIG. 6, the group of receive components identified withinand dashed box 696 is repeated four times, e.g., once for each of fourdistinct RX antennas.

Operation of the system shown in FIG. 6 is described with reference to atransmit operation and with reference to a receive operation. Thedescription of a transmit operation generally corresponds to aleft-to-right progression in FIG. 6 and description of a receiveoperation generally corresponds to a right-to-left progression in FIG.6. With regard to the transmit operation, the crystal oscillator 670generates an analog signal at a frequency of 10 MHz. The 10 MHz signalis provided to the PLL 672, to the frequency synthesizer 680, and to thefrequency divider 684. The PLL uses the 10 MHz signal to generate ananalog signal that is in the 2-6 GHz frequency range. The 2-6 GHz signalis provided to the BPF 674, which filters the input signal and passes asignal in the 2-6 GHz range to the mixer 676. The 2-6 GHz signal is alsoprovided to the mixer 686.

Dropping down in FIG. 6, the 10 MHz signal is used by the frequencysynthesizer 680 to produce a 15 GHz signal. The 15 GHz signal is used bythe frequency doubler 682 to generate a signal at 120 GHz. In anembodiment, the frequency doubler includes a series of three frequencydoublers that each double the frequency, e.g., from 15 GHz to 30 GHz,and then from 30 GHz to 60 GHz, and then from 60 GHz to 120 GHz. The 120GHz signal and the 2-6 GHz signal are provided to the mixer 676, whichmixes the two signals to generate a signal at 122-126 GHz depending onthe frequency of the 2-6 GHz signal. The 122-126 GHz signal output fromthe mixer 676 is provided to the power amplifiers 678, and RF signals inthe 122-126 GHz range are output from the TX antennas 644. In anembodiment, the 122-126 GHz signals are output at 15 dBm (decibels (dB)with reference to 1 milliwatt (mW)). In an embodiment and as describedbelow, the PLL is controlled to generate discrete frequency pulsesbetween 2-6 GHz that are used for stepped frequency transmission.

The 10 MHz signal from the crystal oscillator 670 is also provided tothe frequency divider 684, which divides the frequency down, e.g., from10 MHz to 2.5 MHz via, for example, two divide by two operations, andprovides an output signal at 2.5 MHz to the mixer 686. The mixer 686also receives the 2-6 GHz signal from the BPF 674 and provides a signalat 2-6 GHz+2.5 MHz to the mixer 692 for receive signal processing.

With reference to a receive operation, electromagnetic (EM) energy isreceived at the RX antenna 646 and converted to electrical signals,e.g., voltage and current. For example, electromagnetic energy in the122-126 GHz frequency band is converted to an electrical signal thatcorresponds in frequency (e.g., GHz), magnitude (e.g., power in dBm),and phase to the electromagnetic energy that is received at the RXantenna. The electrical signal is provided to the LNA 688. In anembodiment, the LNA amplifies signals in the 122-126 GHz frequency rangeand outputs an amplified 122-126 GHz signal. The amplified 122-126 GHzsignal is provided to the mixer 690, which mixes the 120 GHz signal fromthe frequency doubler 682 with the received 122-126 GHz signal togenerate a 2-6 GHz signal that corresponds to the electromagnetic energythat was received at the RX antenna. The 2-6 GHz signal is then mixedwith the 2-6 GHz+2.5 MHz signal at mixer 692 to generate a 2.5 MHzsignal that corresponds to the electromagnetic energy that was receivedat the RX antenna. For example, when a 122 GHz signal is beingtransmitted from the TX antennas and received at the RX antenna, themixer 692 receives a 2 GHz signal that corresponds to theelectromagnetic energy that was received at the antenna and a 2 GHz+2.5MHz signal from the mixer 686. The mixer 692 mixes the 2 GHz signal thatcorresponds to the electromagnetic energy that was received at the RXantenna with the 2 GHz+2.5 MHz signal from the mixer 686 to generate a2.5 MHz signal that corresponds to the electromagnetic energy that wasreceived at the RX antenna. The 2.5 MHz signal that corresponds to theelectromagnetic energy that was received at the RX antenna is providedto the IF/BB component 694 for analog-to-digital conversion. Theabove-described receive process can be implemented in parallel on eachof the four receive paths 696. As is described below, the systemdescribed with reference to FIG. 6 can be used to generate variousdiscrete frequencies that can be used to implement, for example, steppedfrequency radar detection. As described above, multiple mixingoperations are performed to implement a sensor system at such a highfrequency, e.g., in the 122-126 GHz range. The multiple mixers andcorresponding mixing operations implement a “compound mixing”architecture that enables use of such high frequencies.

FIG. 7 depicts an embodiment of the IF/BB component 794 shown in FIG. 6.The IF/BB component of FIG. 7 includes similar signal paths 702 for eachof the four receive paths/RX antennas and each signal path includes alow pass filter (LPF) 704, an analog-to-digital converter (ADC) 762, amixer 706, and a decimation filter 708. The operation of receive path 1,RX1, is described.

As described above with reference to FIG. 6, the 2.5 MHz signal frommixer 692 (FIG. 6) is provided to the IF/BB component 694/794, inparticular, to the LPF 704 of the IF/BB component 794. In an embodiment,the LPF filters the 2.5 MHz signal to remove the negative frequencyspectrum and noise outside of the desired bandwidth. After passingthrough the LPF, the 2.5 MHz signal is provided to the ADC 762, whichconverts the 2.5 MHz signal (e.g., IF signal) to digital data at asampling rate of 10 MHz (e.g., as 12-16 bits of “real” data). The mixer706 multiplies the digital data with a complex vector to generate adigital signal (e.g., 12-16 bits of “complex” data), which is alsosampled at 10 MHz. Although the signal is sampled at 10 MHz, othersampling rates are possible, e.g., 20 MHz. The digital data sampled at10 MHz is provided to the decimation filter, which is used to reduce theamount of data by selectively discarding a portion of the sampled data.For example, the decimation filter reduces the amount of data byreducing the sampling rate and getting rid of a certain percentage ofthe samples, such that fewer samples are retained. The reduction insample retention can be represented by a decimation factor, M, and maybe, for example, about 10 or 100 depending on the application, where Mequals the input sample rate divided by the output sample rate.

The output of the decimation filter 706 is digital data that isrepresentative of the electromagnetic energy that was received at thecorresponding RX antenna. In an embodiment, samples are output from theIF/BB component 794 at rate of 1 MHz (using a decimation factor of 10)or at a rate of 100 kHz (using a decimation factor of 100). The digitaldata is provided to a DSP and/or CPU 764 via a bus 710 for furtherprocessing. For example, the digital data is processed to isolate asignal from a particular location, e.g., to isolate signals thatcorrespond to electromagnetic energy that was reflected by the blood ina vein of the person. In an embodiment, signal processing techniques areapplied to implement beamforming, Doppler effect processing, and/orleakage mitigation to isolate a desired signal from other undesiredsignals.

In conventional RF systems, the analog-to-digital conversion processinvolves a high direct current (DC), such that the I (“real”) and Q(“complex”) components of the RF signal at DC are lost at the ADC. Usingthe system as described above with reference to FIGS. 5-7, theintermediate IF is not baseband, so I and Q can be obtained afteranalog-to-digital conversion and digital mixing as shown in FIG. 7.

In an embodiment, digital signal processing of the received signals mayinvolve implementing Kalman filters to smooth out noisy data. In anotherembodiment, digital signal processing of the received signals mayinvolve combining receive chains digitally. Other digital signalprocessing may be used to implement beamforming, Doppler effectprocessing, and ranging. Digital signal processing may be implemented ina DSP and/or in a CPU.

In an embodiment, certain components of the sensor system are integratedonto a single semiconductor substrate and/or onto a single packaged ICdevice (e.g., a packaged IC device that includes multiple differentsemiconductor substrates (e.g., different die) and antennas). Forexample, elements such as the components of the RF front-end 548, and/orcomponents of the digital baseband system 550 (FIGS. 5-7) are integratedonto the same semiconductor substrate (e.g., the same die). In anembodiment, components of the sensor system are integrated onto a singlesemiconductor substrate that is approximately 5 mm×5 mm. In anembodiment, the TX antennas and RX antennas are attached to an outersurface of the semiconductor substrate and/or to an outer surface of anIC package and electrically connected to the circuits integrated intothe semiconductor substrate. In an embodiment, the TX and RX antennasare attached to the outer surface of the IC package such that the TX andRX antenna attachments points are very close to the correspondingtransmit and receive circuits such as the PAs and LNAs. In anembodiment, the semiconductor substrate and the packaged IC deviceincludes outputs for outputting electrical signals to another componentssuch as a DSP, a CPU, and or a bus. In some embodiments, the packaged ICdevice may include the DSP and/or CPU or the packaged IC device mayinclude some DSP and/or CPU functionality.

FIG. 8A depicts an example embodiment of a plan view of an IC device 820that includes two TX antennas 844 and four RX antennas 846 as well assome of the components from the RF front-end and the digital baseband(not shown) as described above with regard to FIGS. 5-7. In FIG. 8A, theouter footprint of the IC device represents a packaged IC device 822 andthe inner footprint (as represented by the dashed box 824) represents asemiconductor substrate that includes circuits that are fabricated intothe semiconductor substrate to conduct and process electrical signalsthat are transmitted by the TX antennas and/or received by the RXantennas. In the embodiment of FIG. 8A, the packaged IC device hasdimensions of 5 mm×5 mm (e.g., referred to as the device “footprint”)and the semiconductor substrate has a footprint that is slightly smallerthan the footprint of the packaged IC device, e.g., the semiconductorsubstrate has dimensions of approximately 0.1-1 mm less than thepackaged IC device on each side. Although not shown, in an exampleembodiment, the packaged IC device has a thickness of approximately0.3-2 mm and the semiconductor substrate has a thickness in the range ofabout 0.1-0.7 mm. In an embodiment, the TX and RX antennas are designedfor millimeter range radio waves, for example, radio waves of 122-126GHz have wavelengths in the range of 2.46 to 2.38 mm. In FIG. 8A, the TXand RX antennas are depicted as square boxes of approximately 1 mm×1 mmand the antennas are all attached on the same planar surface of the ICdevice package. For example, the antennas are attached on the topsurface of the IC package (e.g., on top of a ceramic package material)directly above the semiconductor substrate with conductive vias thatelectrically connect a conductive pad of the semiconductor substrate toa transmission line of the antenna. Although the TX and RX antennas maynot be square, the boxes correspond to an approximate footprint of theTX and RX antennas. In an embodiment, the antennas are microstrip patchantennas and the dimensions of the antennas are a function of thewavelength of the radio waves. Other types of antennas such as dipoleantennas are also possible. FIG. 8B depicts an embodiment of amicrostrip patch antenna 830 that can be used for the TX and/or RXantennas 844 and 846 of the IC device of FIG. 8A. As shown in FIG. 8B,the microstrip patch antenna has a patch portion 832 (with dimensionslength (L)×width (W)) and a microstrip transmission line 834. In someembodiments, microstrip patch antennas have length and width dimensionsof one-half the wavelength of the target radio waves. Thus, microstrippatch antennas designed for radio waves of 122-126 GHz (e.g.,wavelengths in the range of 2.46 to 2.38 mm), the patch antennas mayhave length and width dimensions of around 1.23-1.19 mm, but no morethan 1.3 mm. It is noted that because antenna size is a function ofwavelength, the footprint of the antennas shown in FIGS. 8A and 8B canbe made to be around one-half the size of antennas designed for radiowaves around 60 GHz (e.g., wavelength of approximately 5 mm).Additionally, the small antenna size of the antennas shown in FIGS. 8Aand 8B makes it advantageous to attach all six of the antennas to thetop surface of the package of the IC device within the footprint of thesemiconductor substrate, which makes the packaged IC device more compactthan known devices such as the “Soli” device. That is, attaching all ofthe TX and RX antennas within the footprint of the semiconductorsubstrate (or mostly within the footprint of the semiconductorsubstrate, e.g., greater than 90% within the footprint).

In an embodiment, the RX antennas form a phased antenna array and forthe application of health monitoring it is desirable to have as muchspatial separation as possible between the RX antennas to improveoverall signal quality by obtaining unique signals from each RX antenna.For example, spatial separation of the RX antennas enables improveddepth discrimination to isolate signals that correspond to reflectionsfrom blood in a vein from reflections from other anatomical features.Thus, as shown in FIG. 8A, the RX antennas 846 are located at thecorners of the rectangular shaped IC device. For example, the RXantennas are located flush with the corners of the semiconductorsubstrate 824 and/or flush with the corners of the IC device package orwithin less than about 0.5 mm from the corners of the semiconductorsubstrate 824 and/or from the corners of the IC device package. Althoughthe IC device shown in FIG. 8A has dimensions of 5 mm×5 mm, IC deviceshaving smaller (e.g., approximately 3 mm×3 mm) or larger dimensions arepossible. In an embodiment, the IC device has dimensions of no more than7 mm×7 mm.

In the embodiment of FIG. 8A, the TX antennas 844 are located onopposite sides of the IC chip approximately in the middle between thetwo RX antennas 846 that are on the same side. As shown in FIG. 8A, theTX antenna on the left side of the IC device is vertically aligned withthe two RX antennas on the left side of the IC device and the TX antennaon the right side of the IC device is vertically aligned with the two RXantennas on the right side of the IC device. Although one arrangement ofthe TX and RX antennas is shown in FIG. 8A, other arrangements arepossible.

At extremely high frequencies (e.g., 30-300 GHz) conductor losses can bevery significant. Additionally, conductor losses at extremely highfrequencies are known to be frequency-dependent, with higher frequenciesexhibiting higher conductor losses. In many health monitoringapplications, power, such as battery power, is a limited resource thatmust be conserved. Additionally, for reasons as described above such aslimiting undesired reflections, low power transmissions may be desirablefor health monitoring reasons. Because of the low power environment,conductor losses can severely impact performance of the sensor system.For example, significant conductor losses can occur between the antennasand the conductive pads of the semiconductor substrate, or “die,” andbetween the conductive pads and the transmit/receive components in thedie, e.g., the channel-specific circuits such as amplifiers, filters,mixers, etc. In order to reduce the impact of conductor losses in thesensor system, it is important to locate the antennas as close to thechannel-specific transmit/receive components of the die as possible. Inan embodiment, the transmit and receive components are strategicallyfabricated on the semiconductor substrate in locations that correspondto the desired locations of the antennas. Thus, when the TX and RXantennas are physically and electrically attached to the IC device, theTX and RX antennas are as close as possible to the transmit and receivecomponents on the die, e.g., collocated such that a portion of thechannel specific transmit/receive component overlaps from a plan viewperspective a portion of the respective TX/RX antenna. FIG. 8C depictsan example of the physical layout of circuit components on asemiconductor substrate, such as the semiconductor substrate (die)depicted in FIG. 8A. In the embodiment of FIG. 8C, the die 824 includestwo TX components 854, four RX components 856, shared circuits 860, andan input/output interface (I/O) 862. In the example of FIG. 8C, each TXcomponent includes channel-specific circuits (not shown) such asamplifiers, each RX component includes channel-specific circuits (notshown) such as mixers, filters, and LNAs, and the shared circuitsinclude, for example, a voltage control oscillator (VCO), a localoscillator (LO), frequency synthesizers, PLLs, BPFs, divider(s), mixers,ADCs, buffers, digital logic, a DSP, CPU, or some combination thereofthat may be utilized in conjunction with the channel-specific TX and RXcomponents. As shown in FIG. 8C, the transmit and receive components 854and 856 each include an interface 864 (such as a conductive pad) thatprovides an electrical interface between the circuits on the die and acorresponding antenna. FIG. 8D depicts a packaged IC device 822 similarto the packaged IC device shown in FIG. 8A superimposed over thesemiconductor substrate 824 shown in FIG. 8C. FIG. 8D illustrates thelocations of the TX and RX antennas 844 and 846 relative to the transmitand receive components 854 and 856 of the die (from a plan viewperspective). As illustrated in FIG. 8D, the TX and RX antennas 844 and846 are located directly over the interfaces 864 of the correspondingtransmit and receive components 854 and 856. In an embodiment in whichthe antennas are attached to a top surface of the package (which may beless than 0.5 mm thick), the antennas can be connected to the interfaceof the respective transmit/receive components by a distance that is afraction of a millimeter. In an embodiment, a via that is perpendicularto the plane of the die connects the interface of the transmit/receivecomponent to a transmission line of the antenna. More than one via maybe used when the antenna has more than one transmission line. Such acollocated configuration enables the desired distribution of the TX andRX antennas to be maintained while effectively managing conductor lossesin the system. Such a close proximity between antennas andchannel-specific circuits of the die is extremely important atfrequencies in the 122-126 GHz range and provides an improvement oversensor systems that include conductive traces of multiple millimetersbetween the antennas and the die.

Although the example of FIGS. 8A-8D shows the antennas within thefootprint of the packaged IC device 822, in some other embodiments, theantennas may extend outside the footprint of the die and/or the packagedIC device while still being collocated with the correspondingtransmit/receive components on the die. For example, the antennas may bedipole antennas that have portions of the antennas that extend outsidethe footprint of the die and/or the packaged IC device.

It has been realized that for the application of monitoring a healthparameter such as the blood glucose level in the blood of a person, itis important that the TX antennas are able to illuminate at least onevein near the skin of the person. In order for a TX antenna toilluminate at least one vein near the skin of the person, it isdesirable for at least one of the antennas to be spatially close to avein. Because of variations in the locations of veins relative to thelocation of the monitoring system (e.g., a smartwatch), it has beenfound that a transverse configuration of the TX antennas relative to theexpected location of a vein or veins provides desirable conditions formonitoring a health parameter such as the blood glucose level in theblood of a person. When the wearable device is worn on a portion of alimb such as the wrist, the TX antennas are distributed in a transverseconfiguration relative to the limb and relative to the expected locationof a vein or veins that will be illuminated by the TX antennas.

FIG. 9 depicts an IC device 922 similar to that of FIG. 8A overlaid onthe hand/wrist 912 that is described above with reference to FIG. 2A-2C.The IC device is oriented with regard to the basilic and cephalic veins914 and 916 such that the two TX antennas 944 are configured transverseto the basilic and cephalic veins. That is, the two TX antennas aredistributed transversely relative to the orientation (e.g., the lineardirection) of the vessel or vessels that will be monitored, such as thebasilic and cephalic veins. For example, in a transverse configuration,a straight line that passes through the two TX antennas would betransverse to the vessel or vessels that will be monitored, such as thebasilic and cephalic veins. In an embodiment in which the wearabledevice is worn on the wrist, the transverse configuration of the TXantennas is such that a line passing through both of the TX antennas isapproximately orthogonal to the wrist and approximately orthogonal tothe orientation of the vessel or vessels that will be monitored, such asthe basilic and cephalic veins. For example, a line passing through bothof the TX antennas and the orientation of the vessel or vessels thatwill be monitored, such as the basilic and cephalic veins, may bewithout about 20 degrees from orthogonal.

FIG. 10 depicts an IC device 1022 similar to that of FIG. 8A overlaid onthe back of the smartwatch 1000 described above with reference to FIGS.1A and 1B. As shown in FIGS. 9 and 10, the two TX antennas areconfigured such that when the smartwatch is worn on the wrist, the twoTX antennas are transverse to veins such as the basilic and cephalicveins that run parallel to the length of the arm and wrist.

FIGS. 11 and 12 are provided to illustrate the expanded illuminationvolume that can be achieved by a sensor system 1010 that includes atransverse TX antenna configuration. FIG. 11 depicts a side view of asensor system in a case in which the two TX antennas 1044 are configuredparallel to veins such as the basilic and cephalic veins of a personwearing the smartwatch 1000. In the view shown in FIG. 11, the two TXantennas are in-line with each other such that only one of the two TXantennas is visible from the side view. When the TX antennas transmitmillimeter range radio waves, the electromagnetic energy may have atwo-dimensional (2D) illumination pattern as illustrated by dashed line1020. Given the two-dimensional pattern as illustrated in FIG. 11, thetwo TX antennas illuminate an area that has a maximum width in thetransverse direction (transverse to veins that run parallel to thelength of the arm and wrist and referred to herein as the transversewidth) identified by arrow 1022. Although the illumination pattern isdescribed and illustrated in two dimensions (2D), it should beunderstood that illumination actually covers a 3D space or volume.

FIG. 12 depicts the same side view as shown in FIG. 11 in a case inwhich the two TX antennas 1044 are configured transverse to veins suchas the basilic and cephalic veins of a person wearing the smartwatch1000. In the view shown in FIG. 12, the two TX antennas are spatiallyseparated from each other such that both of the TX antennas are visiblefrom the side view. When the TX antennas transmit millimeter range radiowaves, the electromagnetic energy may have a 2D illumination pattern asillustrated by dashed lines 1024. Given the 2D elimination patterns ofthe two TX antennas, the two TX antennas combine to illuminate an areathat has a width in the transverse direction (transverse width)identified by arrow 1026, which is wider than the transverse width forthe TX antenna configuration shown in FIG. 11 (e.g., almost twice aswide). A wider illumination area improves the coverage area for thesensor system 1010 and increases the likelihood that the sensor systemwill illuminate a vein in the person wearing the smartwatch. Anincreased likelihood that a vein is illuminated can provide morereliable feedback from the feature of interest (e.g., blood in the vein)and thus more reliable monitoring results. Additionally, a widerillumination area can increase the power of the radio waves thatilluminate a vein, resulting in an increase in the power of theelectromagnetic energy that is reflected from the vein, which canimprove the quality of the received signals.

It has been established that the amount of glucose in the blood (bloodglucose level) affects the reflectivity of millimeter range radio waves.However, when millimeter range radio waves are applied to the human body(e.g., at or near the skin surface), electromagnetic energy is reflectedfrom many objects including the skin itself, fibrous tissue such asmuscle and tendons, and bones. In order to effectively monitor a healthparameter such as the blood glucose level of a person, electricalsignals that correspond to electromagnetic energy that is reflected fromblood (e.g., from the blood in a vein) should be isolated fromelectrical signals that correspond to electromagnetic energy that isreflected from other objects such as the skin itself, fibrous tissue,and bone, as well as from electrical signals that correspond toelectromagnetic energy that is emitted directly from the TX antennas(referred to herein as electromagnetic energy leakage or simply as“leakage”) and received by an antenna without passing through the skinof the person.

Various techniques that can be implemented alone or in combination toisolate electrical signals that correspond to reflections from bloodfrom other electrical signals that correspond to other reflections (suchas reflections from bone and/or fibrous tissue such as muscle andtendons) and/or signals that correspond to leakage are described below.Such techniques relate to and/or involve, for example, transmissioncharacteristics, beamforming, Doppler effect processing, leakagemitigation, and antenna design.

As is known in the field, radar detection involves transmittingelectromagnetic energy and receiving reflected portions of thetransmitted electromagnetic energy. Techniques for transmittingelectromagnetic energy in radar systems include impulse, chirp, andstepped frequency techniques.

FIGS. 13A-13C depict frequency versus time graphs of impulse, chirp, andstepped frequency techniques for transmitting electromagnetic energy ina radar system. FIG. 13A depicts a radar transmission technique thatinvolves transmitting pulses of electromagnetic energy at the samefrequency for each pulse, referred to as “impulse” transmission. In theexample of FIG. 13A, each pulse is at frequency, f₁, and lasts for aconstant interval of approximately 2 ns. The pulses are each separatedby approximately 2 ns.

FIG. 13B depicts a radar transmission technique that involvestransmitting pulses of electromagnetic energy at an increasing frequencyfor each interval, referred to herein as “chirp” transmission. In theexample of FIG. 13B, each chirp increases in frequency from frequency f₀to f₁ over an interval of 2 ns and each chirp is separated by 2 ns. Inother embodiments, the chirps may be separated by very short intervals(e.g., a fraction of a nanosecond) or no interval.

FIG. 13C depicts a radar transmission technique that involvestransmitting pulses of electromagnetic energy at the same frequencyduring a particular pulse but at an increased frequency frompulse-to-pulse, referred to herein as a “stepped frequency” transmissionor a stepped frequency pattern. In the example of FIG. 13C, each pulsehas a constant frequency over the interval of the pulse (e.g., over 2ns), but the frequency increases by an increment of Δf frompulse-to-pulse. For example, the frequency of the first pulse is f₀, thefrequency of the second pulse is f₀+Δf, the frequency of the third pulseis f₀+2Δf, and the frequency of the fourth pulse is f₀+3Δf, and so on.

In an embodiment, the sensor system described herein is operated usingstepped frequency transmission. Operation of the sensor system usingstepped frequency transmission is described in more detail below. FIG.14 depicts a burst of electromagnetic energy using stepped frequencytransmission. The frequency of the pulses in the burst can be expressedas:

f _(n) =f ₀ +nΔf

where f₀=starting carrier frequency, Δf=step size, r=pulse length(active, per frequency), T=repetition interval, n=1, . . . N, each burstconsists of N pulses (frequencies) and a coherent processing interval(CPI)=N·T=1 full burst.

Using stepped frequency transmission enables relatively high rangeresolution. High range resolution can be advantageous when trying tomonitor a health parameter such as the blood glucose level in a veinthat may, for example, have a diameter in the range of 1-4 mm. Forexample, in order to effectively isolate a signal that corresponds toreflections of electromagnetic energy from the blood in a 1-4 mmdiameter vein, it is desirable to have a high range resolution, which isprovided by the 122-126 GHz frequency range.

Using stepped frequency transmission, range resolution can be expressedas:

ΔR=c/2B

wherein c=speed of light, B=effective bandwidth. The range resolutioncan then be expressed as:

ΔR=c/2N·Δf

wherein B=N·Δf. Thus, range resolution does not depend on instantaneousbandwidth and the range resolution can be increased arbitrarily byincreasing N·Δf.

In an embodiment, the electromagnetic energy is transmitted from the TXantennas in the frequency range of approximately 122-126 GHz, whichcorresponds to a total bandwidth of approximately 4 GHz, e.g., B=4 GHz.FIG. 15A depicts a graph of the transmission bandwidth, B, oftransmitted electromagnetic energy in the frequency range of 122-126GHz. Within a 4 GHz bandwidth, from 122-126 GHz, discrete frequencypulses can be transmitted. For example, in an embodiment, the number ofdiscrete frequencies that can be transmitted ranges from, for example,64-256 discrete frequencies. In a case with 64 discrete frequency pulsesand a repetition interval, T, over 4 GHz of bandwidth, the step size,Δf, is 62.5 MHz (e.g., 4 GHz of bandwidth divided by 64=62.5 MHz) and ina case with 256 discrete frequency pulses and a repetition interval, T,over 4 GHz of bandwidth, the step size, Δf, is 15.625 MHz (e.g., 4 GHzof bandwidth divided by 256=15.625 MHz). FIG. 15B depicts a graph ofstepped frequency pulses that have a repetition interval, T, and a stepsize, Δf, of 62.5 MHz (e.g., 4 GHz of bandwidth divided by 64=62.5 MHz).As described above, an example sensor system has four RX antennas.Assuming a discrete frequency can be received on each RX antenna,degrees of freedom (DOF) of the sensor system in the receive operationscan be expressed as: 4 RX antennas×64 discrete frequencies=256 DOF; and4 RX antennas×256 discrete frequencies=1K DOF. The number of degrees offreedom (also referred to as “transmission frequency diversity”) canprovide signal diversity, which can be beneficial in an environment suchas the anatomy of a person. For example, the different discretefrequencies may have different responses to the different anatomicalfeatures of the person. Thus, greater transmission frequency diversitycan translate to greater signal diversity, and ultimately to moreaccurate health monitoring.

One feature of a stepped frequency transmission approach is that thesensor system receives reflected electromagnetic energy at basically thesame frequency over the repetition interval, T. That is, as opposed tochirp transmission, the frequency of the pulse does not change over theinterval of the pulse and therefore the received reflectedelectromagnetic energy is at the same frequency as the transmittedelectromagnetic energy for the respective interval. FIG. 16A depicts afrequency versus time graph of transmission pulses, with transmit (TX)interval and receive (RX) intervals identified relative to the pulses.As illustrated in FIG. 16A, RX operations for the first pulse occurduring the pulse length, τ, of repetition interval, T, and during theinterval between the next pulse. FIG. 16B depicts an amplitude versustime graph of the transmission waveforms that corresponds to FIG. 16A.As illustrated in FIG. 16B, the amplitude of the pulses is constantwhile the frequency increases by Δf at each repetition interval, T.

In an embodiment, the power of the transmitted electromagnetic energycan be set to achieve a desired penetration depth and/or a desiredillumination volume. In an embodiment, the transmission power from theTX antennas is about 15 dBm.

In an embodiment, electromagnetic energy can be transmitted from the TXantennas one TX antenna at a time (referred to herein as “transmitdiversity”). For example, a signal is transmitted from a first one ofthe two TX antennas while the second one of the two TX antennas is idleand then a signal is transmitted from the second TX antenna while thefirst TX antenna is idle. Transmit diversity may reveal thatillumination from one of the two TX antennas provides a higher qualitysignal than illumination from the other of the two TX antennas. This maybe especially true when trying to illuminate a vein whose location mayvary from person to person and/or from moment to moment (e.g., dependingon the position of the wearable device relative to the vein). Thus,transmit diversity can provide sets of received signals that areindependent of each other and may have different characteristics, e.g.,signal power, SNR, etc.

Some theory related to operating the sensor system using a steppedfrequency approach is described with reference to FIG. 17, whichillustrates operations related to transmitting, receiving, andprocessing phases of the sensor system operation. With reference to theupper portion of FIG. 17, a time versus amplitude graph of a transmittedsignal burst, similar to the graph of FIG. 16B, is shown. The graphrepresents the waveforms of five pulses of a burst at frequencies off₀,f₀+Δf, f₀+2Δf, f₀+3Δf, and f₀+4Δf.

The middle portion of FIG. 17 represents values of received signals thatcorrespond to the amplitude, phase, and frequency of each pulse in theburst of four pulses. In an embodiment, received signals are placed inrange bins such that there is one complex sample per range bin perfrequency. Inverse Discrete Fourier Transforms (IDFTs) are thenperformed on a per-range bin basis to determine range information. Thebottom portion of FIG. 17 illustrates an IDFT process that produces asignal that corresponds to the range of a particular object. Forexample, the range may correspond to a vein such as the basilic vein. Inan embodiment, some portion of the signal processing is performeddigitally by a DSP or CPU. Although one example of a signal processingscheme is described with reference to FIG. 17, other signal processingschemes may be implemented to isolate signals that correspond toreflections from blood in a vein (such as the basilic vein) from signalsthat correspond to reflections from other undesired anatomical features(such as tissue and bones) and from signals that correspond to leakagefrom the TX antennas.

Beamforming is a signal processing technique used in sensor arrays fordirectional signal transmission and/or reception. Beamforming can beimplemented by combining elements in a phased antenna array in such away that signals at particular angles experience constructiveinterference while other signals experience destructive interference.Beamforming can be used in both transmit operations and receiveoperations in order to achieve spatial selectivity, e.g., to isolatesome received signals from other received signals. In an embodiment,beamforming techniques are utilized to isolate signals that correspondto reflections from blood in a vein (such as the basilic vein) fromsignals that correspond to reflections from other undesired anatomicalfeatures (such as tissue and bones) and from signals that correspond toleakage from the TX antennas. An example of the concept of beamformingas applied to blood glucose monitoring using a wearable device such as asmartwatch is illustrated in FIG. 18. In particular, FIG. 18 depicts anexpanded view of the anatomy of a wrist, similar to that described abovewith reference to FIGS. 2A-4D, relative to RX antennas 1846 of a sensorsystem 1810 that is integrated into a wearable device such as asmartwatch 1800. The anatomical features of the wrist that areillustrated in FIG. 18 include the skin 1822, a vein such as the basilicvein 1816, the radius bone 1834, and the ulna bone 1836. FIG. 18 alsoillustrates 2D representations of reception beams 1850 (although itshould be understood that the beams occupy a 3D space/volume) thatcorrespond to electromagnetic energy that is reflected from the blood inthe basilic vein to the respective RX antenna.

In an embodiment, a beamforming technique involves near-fieldbeamforming, where each RX antenna of the phased antenna array issteered independently to a different angle as opposed to far-fieldbeamforming where all of the antennas in a phased antenna array aresteered collectively to the same angle. For example, near-fieldbeamforming is used when the target is less than about 4-10 wavelengthsfrom the phased antenna array. In the case of a sensor system operatingat 122-126 GHz, 4-10 wavelengths is approximately within about 10-25 mmfrom the phased antenna array. In the case of monitoring a healthparameter related to blood, the blood vessels that are monitored (e.g.,the basilic and/or cephalic veins) are likely to be less than 10-25 mmfrom the phase antenna array. Thus, in an embodiment, near-fieldbeamforming techniques are used to isolate desired signals (e.g.,signals that correspond to reflections from blood in a vein such as thebasilic vein) from undesired signals (e.g., signals that correspond toreflections from other undesired anatomical features, such as tissue andbones, and from signals that correspond to leakage from the TXantennas). Beamforming can be accomplished in digital, in analog, or ina combination of digital and analog signal processing. In an embodiment,the ranging technique described above, which utilizes steppedfrequencies, is used in combination with beamforming to isolate signalsthat correspond to the reflection of electromagnetic energy from thebasilic vein.

The Doppler effect relates to the change in frequency or wavelength of awave (e.g., an electromagnetic wave) in relation to an observer, whichis moving relative to the source of the wave. The Doppler effect can beused to identify fluid flow by sensing the shift in wavelength ofreflections from particles moving with the fluid flow. In accordancewith an embodiment of the invention, signal processing based on theDoppler effect is applied to signals received by the sensor system toisolate signals that correspond to reflections from flowing blood fromsignals that correspond to reflections from objects that are stationary,at least with respect to the flowing blood. As described above,millimeter wave radio waves are transmitted below the skin to illuminateanatomical features below the skin. In the area of the body around thewrist, blood flowing through veins such as the basilic and cephalicveins is moving relative to the other anatomical features in the area.Thus, Doppler effect theory and corresponding signal processing is usedto filter for those signals that correspond to movement (movementrelative to other signals that correspond to stationary objects). In thehealth monitoring application as described herein, the signals thatcorrespond to the flowing blood can be identified by applying theDoppler effect theory to the signal processing to isolate the signalsthat correspond to the flowing blood. The isolated signals can then beused to measure a health parameter such as blood glucose level.

FIG. 19 illustrates an IC device 1922 similar to the IC device 822 shownin FIG. 8A relative to a vein 1916 such as the basilic or cephalic veinin the wrist area of a person. FIG. 19 also illustrates the flow ofblood through the vein relative to the IC device. Because the blood ismoving relative to the TX and RX antennas 1944 and 1946 of the sensorsystem, Doppler effect theory can be applied to signal processing of thereceived signals to isolate the signals that correspond to the flowingblood from the signals that correspond to objects that are stationaryrelative to the flowing blood. For example, received signals thatcorrespond to flowing blood are isolated from received signals thatcorrespond to stationary objects such as bone and fibrous tissue such asmuscle and tendons. In an embodiment, Doppler processing involvesperforming a fast Fourier transform (FFT) on samples to separate thesamples into component Doppler shift frequency bins. Frequency bins thatrepresent no frequency shift can be ignored (as they correspond toreflections from stationary objects) and frequency bins that represent afrequency shift (which corresponds to reflections from a moving object)can be used to determine a health parameter. That is, Doppler effectprocessing can be used to isolate signals that represent no frequencyshift (as they correspond to reflections from stationary objects) fromfrequency bins that represent a frequency shift (which correspond toreflections from a moving object). In an embodiment, Doppler effectsignal processing may involve sampling over a relatively long period oftime to achieve small enough velocity bins to decipher relativemovement. Thus, Doppler effect theory and corresponding signalprocessing can be used to filter for only those signals that correspondto movement (movement relative to the other received signals). Such anapproach allows signals that correspond to reflections from flowingblood, e.g., blood in a vein, to be isolated from other signals, e.g.,signals that correspond to stationary object. In an embodiment, Dopplersignal processing is performed digitally by a DSP and/or by a CPU.

With reference to FIG. 8A, during operation of the IC device 822, someelectromagnetic energy that is emitted from the TX antennas 844 will bereceived directly by at least one of the RX antennas 846 without firstpassing through the skin of the person. Signals that correspond to suchelectromagnetic energy do not correspond to a health parameter that isto be monitored and are referred to herein as electromagnetic energyleakage or simply as “leakage.” In an embodiment, various signalprocessing techniques may be implemented to mitigate the effects ofleakage. For example, signals that correspond to leakage should beisolated from signals that correspond to reflections of radio waves fromblood in a vein. In an embodiment, leakage is mitigated by applyingsignal processing to implement beamforming, Doppler effect processing,range discrimination or a combination thereof. Other techniques such asantenna design and antenna location can also be used to mitigate theeffects of leakage.

In an embodiment, signal processing to isolate signals that correspondto reflections of radio waves from blood in a vein from signals thatcorrespond to reflections of radio waves from other anatomical objects(such as bone and fibrous tissue such as muscle and tendons) and fromsignals that correspond to leakage can be implemented in part or in fulldigitally by a DSP. FIG. 20 is an embodiment of a DSP 2064 that includesa Doppler effect component 2070, a beamforming component 2072, and aranging component 2074. In an embodiment, the Doppler effect componentis configured to implement digital Doppler effect processing, thebeamforming component is configured to implement digital beamforming,and the ranging component is configured to implement digital ranging.Although the DSP is shown as including the three components, the DSP mayinclude fewer components and the DSP may include other digital signalprocessing capability. The DSP may include hardware, software, and/orfirmware or a combination thereof that is configured to implement thedigital signal processing that is described herein. In an embodiment,the DSP may be embodied as an ARM processor (Advanced RISC (reducedinstruction set computing) Machine). In some embodiments, components ofa DSP can be implemented in the same IC device as the RF front-end andthe TX and RX antennas. In other embodiments, components of the DSP areimplemented in a separate IC device or IC devices.

In an embodiment, the transmission of millimeter radio waves and theprocessing of signals that correspond to received radio waves is adynamic process that operates to locate signals corresponding to thedesired anatomy (e.g., signals that correspond to reflections of radiowaves from a vein) and to improve the quality of the desired signals(e.g., to improve the SNR). For example, the process is dynamic in thesense that the process is an iterative and ongoing process as thelocation of the sensor system relative to a vein or veins changes.

Although the techniques described above are focused on monitoring theblood glucose level in a person, the disclosed techniques are alsoapplicable to monitoring other parameters of a person's health such as,for example, blood pressure and heart rate. For example, thereflectively of blood in a vessel such as the basilic vein will changerelative to a change in blood pressure. The change in reflectivity asmonitored by the sensor system can be correlated to a change in bloodpressure and ultimately to an absolute value of a person's bloodpressure. Additionally, monitored changes in blood pressure can becorrelated to heart beats and converted over time to a heart rate, e.g.,in beats per minute. In other embodiments, the disclosed techniques canbe used to monitor other parameters of a person's health that areaffected by the chemistry of the blood. For example, the disclosedtechniques may be able to detect changes in blood chemistry thatcorrespond to the presence of foreign chemicals such as alcohol,narcotics, cannabis, etc. The above-described techniques may also beable to monitor other parameters related to a person, such as biometricparameters.

In an embodiment, health monitoring using the techniques describedabove, may involve a calibration process. For example, a calibrationprocess may be used for a particular person and a particular monitoringdevice to enable desired monitoring quality.

The above-described techniques are used to monitor a health parameter(or parameters) related to blood in a blood vessel or in blood vesselsof a person. The blood vessels may include, for example, arteries,veins, and/or capillaries. The health monitoring technique can targetblood vessels other than the basilic and/or cephalic veins. For example,other near-surface blood vessels (e.g., blood vessels in thesubcutaneous layer) such as arteries may be targeted. Additionally,locations other than the wrist area can be targeted for healthmonitoring. For example, locations in around the ear may be a desirablelocation for health monitoring, including, for example, the superficialtemporal vein and/or artery and/or the anterior auricular vein orartery. In an embodiment, the sensor system may be integrated into adevice such as a hearing aid or other wearable device that is attachedto the ear or around or near the ear. In another embodiment, locationsin and around the elbow joint of the arm may be a desirable location forhealth monitoring. For example, in or around the basilica vein or thecephalic vein at or near the elbow.

Although the techniques are described as using a frequency range of122-126 GHz, some or all of the above-described techniques may beapplicable to frequency ranges other than 122-126 GHz. For example, thetechniques may be applicable to frequency ranges around 60 GHz. Inanother embodiment, the techniques described herein may be applicable tothe 2-6 GHz frequency range. For example, a system similar to thatdescribed with reference to FIG. 6 may be used to implement healthmonitoring by transmitting and receiving RF energy in the 2-6 GHz range.In still another embodiment, multiple non-contiguous frequency rangesmay be used to implement health monitoring. For example, healthmonitoring may be implemented using both the 2-6 GHz frequency range andthe 122-126 GHz frequency range. For example, in an embodiment, steppedfrequency scanning in implemented in the lower frequency range and thenin the higher frequency range, or vice versa. Using multiplenon-contiguous frequency ranges (e.g., both the 2-6 GHz frequency rangeand the 122-126 GHz frequency range) may provide improved accuracy ofhealth monitoring.

In an embodiment, the sensor system may be embedded into a differentlocation in a monitoring device. For example, in an embodiment, a sensorsystem (or a portion of the sensor system such as IC device as shown inFIG. 8A) is embedded into an attachment device such as the strap of asmartwatch so that the sensor system can target a different blood vesselin the person. For example, the sensor system may be embedded into thestrap of a smartwatch so that a blood vessel at the side area of thewrist and/or at the anterior area of the wrist can be monitored. In suchan embodiment, the strap may include conductive signal paths thatcommunicate signals between the sensor IC device and the processor ofthe smartwatch.

FIG. 21 is a process flow diagram of a method for monitoring a healthparameter in a person. At block 2102, millimeter range radio waves aretransmitted over a three-dimensional (3D) space below the skin surfaceof a person. At block 2104, radio waves are received on multiple receiveantennas, the received radio waves including a reflected portion of thetransmitted radio waves. At block 2106, a signal is isolated from aparticular location in the 3D space in response to receiving the radiowaves on the multiple receive antennas. At block 2108, a signal thatcorresponds to a health parameter in the person is output in response tothe isolated signal. In an embodiment, the health parameter is bloodglucose level. In other embodiments, the health parameter may be bloodpressure or heart rate.

In an embodiment, health monitoring information that is gathered usingthe above-described techniques can be shared. For example, the healthmonitoring information can be displayed on a display device and/ortransmitted to another computing system via, for example, a wirelesslink.

As mentioned above, locations in around the ear may be desirable forhealth monitoring, including, for example, the superficial temporalartery or vein, the anterior auricular artery or vein, and/or theposterior auricular artery. FIG. 22A depicts a side view of the areaaround a person's ear 2200 with the typical approximate locations ofveins and arteries, including the superficial temporal artery 2202, thesuperficial temporal vein 2204, the anterior auricular artery 2206 andvein 2208, the posterior auricular artery 2210, the occipital artery2212, the external carotid artery 2214, and the external jugular vein2216. In an embodiment, a sensor system, such as the sensor systemdescribed herein, may be integrated into a device such as a hearing aidor another wearable device that is attached to the ear or around or nearthe ear. FIG. 22B depicts an embodiment of system 2250 in which at leastelements of an RF front-end 2222 (including the transmit and receiveantennas and corresponding transmit and receive components as shown inFIGS. 5-7) are located separate from a housing 2252 that includes, forexample, a digital processor, wireless communications capability, and asource of electric power, all of which are enclosed within the housing.For example, components of the digital baseband system as shown in FIG.5 may be enclosed within the housing and the housing is connected to theRF front-end by a communications medium 2254, such as a conductive wireor wires. In an embodiment, the housing 2252 is worn behind the ear 2200similar to a conventional hearing aid and the RF front-end 2222 islocated near a blood vessel that is around the ear. For example, the RFfront-end may include adhesive material that enables the RF front-end tobe adhered to the skin near a blood vessel such as, for example, thesuperficial temporal artery 2202 or vein 2204, the anterior auricularartery 2206 or vein 2208, and/or the posterior auricular artery 2210.FIG. 22C illustrates how a device, such as the device depicted in FIG.22B, may be worn near the ear 2200 of a person similar to how aconventional hearing aid is worn. FIG. 22C also shows the RF front-end2222 relative to the superficial temporal artery 2202 and thesuperficial temporal vein 2204 as shown in FIG. 22C. In an embodiment,the sensor system may be integrated with a conventional hearing aid toprovide both hearing assistance and health monitoring. For example, theintegrated system may include a housing, a speaker that is inserted intothe ear, and an RF front-end that is attached to the skin around the earand near to a blood vessel. In other embodiments, a sensor system may beintegrated into ear buds or into some other type of device that is wornaround or near the ear.

Although the magnitude of the reflected RF energy (also referred to asamplitude) that is received by the sensor system has been found tocorrespond to a health parameter, such as blood glucose level, it hasfurther been found that the combination of the amplitude and the phaseof the reflected RF energy can provide improved correspondence to ahealth parameter, such as a blood glucose level. Thus, in an embodiment,a value that corresponds to a health parameter of a person is generatedin response to amplitude and phase data that is generated in response toreceived radio waves. For example, the value that corresponds to ahealth parameter may be a value that indicates a blood glucose level inmg/dL or some other indication of the blood glucose level, a value thatindicates a person's heart rate (e.g., in beats per minute), and/or avalue that indicates a person's blood pressure (e.g., in millimeters ofmercury, mmHg). In an embodiment, a method for monitoring a healthparameter (e.g., blood glucose level) in a person involves transmittingradio waves below the skin surface of a person and across a range ofstepped frequencies, receiving radio waves on a two-dimensional array ofreceive antennas, the received radio waves including a reflected portionof the transmitted radio waves across the range of stepped frequencies,generating data that corresponds to the received radio waves, whereinthe data includes amplitude and phase data across the range of steppedfrequencies, and determining a value that is indicative of a healthparameter in the person in response to the amplitude and phase data. Inan embodiment, the phase data corresponds to detected shifts in sinewaves that are received at the sensor system. In another embodiment, avalue that is indicative of a health parameter in the person may bedetermined in response to phase data but not in response to amplitudedata.

Additionally, it has been found that certain step sizes in steppedfrequency scanning can provide good correspondence in health parametermonitoring. In an embodiment, the frequency range that is scanned usingstepped frequency scanning is on the order of 100 MHz in the 122-126 GHzrange and the step size is in the range of 100 kHz-1 MHz. For example,in an embodiment, the step size over the scanning range is around 100kHz (±10%).

Although the amplitude and phase of the reflected RF energy that isreceived by the sensor system has been found to correspond to a healthparameter, such as blood glucose level, it has further been found thatthe combination of the amplitude and phase of the reflected RF energyand some derived data, which is derived from the amplitude and/or phasedata, can provide improved correspondence to a health parameter, such asblood glucose level. Thus, in an embodiment, some data is derived fromthe amplitude and/or phase data that is generated by the sensor systemin response to the received RF energy and the derived data is used,often in conjunction with the amplitude and/or phase data, to determinea value that corresponds to a health parameter (e.g., the blood glucoselevel) of a person. For example, the data derived from the amplitudeand/or phase data may include statistical data such as the standarddeviation of the amplitude over a time window and/or the standarddeviation of the phase over a time window. In an embodiment, data can bederived from the raw data on a per-receive antenna basis or aggregatedamongst the set of receive antennas. In a particular example, it hasbeen found that the amplitude, phase, and the standard deviation ofamplitude over a time window (e.g., a time window of 1 second)corresponds well to blood glucose levels.

In an embodiment, a method for monitoring a health parameter (e.g.,blood glucose level) in a person involves transmitting radio waves belowthe skin surface of the person and across a range of steppedfrequencies, receiving radio waves on a two-dimensional array of receiveantennas, the received radio waves including a reflected portion of thetransmitted radio waves across the range of stepped frequencies,generating data that corresponds to the received radio waves, whereinthe data includes amplitude and phase data, deriving data from at leastone of the amplitude and phase data, and determining a value that isindicative of a health parameter in the person in response to thederived data. In an embodiment, the value is determined in response tonot only the derived data but also in response to the amplitude data andthe phase data. In an embodiment, the derived data is a statistic thatis derived from amplitude and/or phase data that is generated over atime window. For example, the statistic is one of a standard deviation,a moving average, and a moving mean. In other embodiments, the deriveddata may include multiple statistics derived from the amplitude and/orphase data. In an embodiment, a value that is indicative of a healthparameter is determined in response to a rich set of parametersassociated with the stepped frequency scanning including the scanningfrequency, the detected amplitudes and phases of the received RF energy,data derived from the detected amplitudes and phases, the state of thetransmit components, and the state of the receive components.

Using a sensor system, such as the sensor system described above, thereare various parameters to be considered in the stepped frequencyscanning process. Some parameters are fixed during operation of thesensor system and other parameters may vary during operation of thesensor system. Of the parameters that may vary during operation of thesensor system, some may be controlled and others are simply detected.FIG. 23 is a table of parameters related to stepped frequency scanningin a system such as the above-described system. The table includes anidentification of various parameters and an indication of whether thecorresponding parameter is fixed during operation (e.g., fixed as aphysical condition of the sensor system) or variable during operationand if the parameter is variable, whether the parameter is controlled,or controllable, during operation or simply detected during operation.In the table of FIG. 23, “Time” refers to an aspect of time such as anabsolute moment in time relative to some reference (or may refer to atime increment, e.g., Δt). In an embodiment, the time corresponds to allof the other parameters in the table. That is, the state or value of allof the other parameters in the table is the state or value at that timein the stepped frequency scanning operation. “TX/RX frequency” refers tothe transmit/receive frequency of the sensor system at the correspondingtime as described above with reference to, for example, FIG. 6. The TX1and TX2 state refers to the state of the corresponding transmitter(e.g., whether or not the corresponding power amplifiers (PAs) are on oroff) at the corresponding time. In an embodiment, RF energy transmittedfrom the transmission antennas can be controlled byactivating/deactivating the corresponding PAs. The RX1 and RX2 staterefers to the state of the corresponding receive paths (e.g., whether ornot components of the corresponding receive paths are active orinactive, which may involve powering on/off components in the receivepath) at the corresponding time. In an embodiment, the receiving of RFenergy on the receive paths can be controlled by activating/deactivatingcomponents of the corresponding receive paths. The RX detected amplituderefers to the amplitude of the received signals at the correspondingreceive path and at the corresponding time and the RX detected phaserefers to the phase (or phase shift) of the received signals at thecorresponding receive path and at the corresponding time. The TX and RXantenna 2D position refers to information about the 2D position of theantennas in the sensor system (e.g., the positions of the antennasrelative to each other or the positions of the antennas relative to acommon location) and the antenna orientation refers to antennacharacteristics that may be specific to a particular polarizationorientation. For example, a first set of antennas may be configured forvertical polarization while a second set of antennas is configured forhorizontal polarization in order to achieve polarization diversity.Other antenna orientations and/or configurations are possible. Asindicated in the table, antenna position and antenna orientation arefixed during stepped frequency scanning.

FIG. 24 is a table of parameters similar to the table of FIG. 23 inwhich examples are associated with each parameter for a given step in astepped frequency scanning operation in order to give some context tothe table. As indicated in FIG. 24, the time is “t1” (e.g., someabsolute time indication or a time increment) and the operatingfrequency is “X GHz,” e.g., in the range of 2-6 GHz or 122-126 GHz. Inthe example of FIG. 24, TX1, RX1, and RX4 are active and TX2, RX2, andRX3 are inactive during this step in the stepped frequency scanningoperation (e.g., at time t1). The detected amplitudes of RX1 and RX4 areindicated as “ampl1” and “ampl4” and the detected phases of RX1 and RX4are indicated as “ph1” and “ph4.” The detected amplitudes and phases ofRX2 and RX3 are indicated as “n/a” since the receive paths are inactive.The positions of the transmit and receive antennas are indicated in thelower portion of the table and correspond to the configuration describedabove with reference to FIGS. 8A-8D and the antenna orientations areevenly distributed amongst vertical and horizontal orientations so as toenable polarization diversity. FIG. 25 depicts an embodiment of the ICdevice 820 from FIG. 8A in which the antenna polarization orientation isillustrated by the orientation of the transmit and receive antennas 844and 846, respectively. In FIG. 25, rectangles with the long edgesoriented vertically represent a vertical polarization orientation (e.g.,antennas TX1, RX1, and RX4) and rectangles with the long edges orientedhorizontally represent a horizontal polarization orientation (e.g.,antennas TX2, RX2, and RX3). FIG. 24 reflects the same polarizationorientations in which TX1 is configured to vertically polarize thetransmitted RF energy and RX1 and RX4 are configured to receivevertically polarized RF energy and TX2 is configured to horizontallypolarize the transmitted RF energy and RX2 and RX3 are configured toreceive horizontally polarized RF energy. Although FIG. 24 is providedas an example, the parameter states of the variable parameters areexpected to change during stepped frequency scanning and the fixedparameters may be different in different sensor system configurations.

In an embodiment, during a stepped frequency scanning operation, certaindata, referred to herein as “raw data,” is generated. For example, theraw data is generated as digital data that can be further processed by adigital data processor. FIG. 26 is a table of raw data (e.g., digitaldata) that is generated during stepped frequency scanning. The raw datadepicted in FIG. 26 includes variable parameters of time, TX/RXfrequency, RX1 amplitude/phase, RX2 amplitude/phase, RX3amplitude/phase, and RX4 amplitude/phase. In the example of FIG. 26, theraw data corresponds to a set of data, referred to as a raw data record,which corresponds to one step in the stepped frequency scanning. Forexample, the raw data record corresponds to a particular frequency pulseas shown and described above with reference to FIG. 17. In anembodiment, a raw data record also includes some or all of theparameters identified in FIGS. 23 and 24. For example, the raw datarecord may include other variable and/or fixed parameters thatcorrespond to the stepped frequency scanning operation. In anembodiment, multiple raw data records are accumulated and processed by adigital processor, which may include a DSP, an MCU, and/or a CPU asdescribed above, for example, with reference to FIG. 5. Raw data (e.g.,in the form of raw data records) may be used for machine learning.

As described above, it has been found that the combination of theamplitude and phase of reflected RF energy and some derived data, whichis derived from amplitude and/or phase data (e.g., from the “raw data”),can provide improved correspondence to a health parameter, such as bloodglucose level. Thus, in an embodiment, some data is derived from theamplitude and/or phase data that is generated by the sensor system inresponse to the received RF energy and the derived data is used, oftenin conjunction with the amplitude and/or phase data, to determine avalue that corresponds to a health parameter (e.g., the blood glucoselevel) of a person. For example, the data is derived from the raw datarecords that include the data depicted in FIGS. 23, 24, and 26. Forexample, raw data records are accumulated over time and statistical datais derived from the accumulated raw data records. The statistical data,typically along with at least some portion of the raw data, is then usedto determine a value of a health parameter of a person.

Although it has been found that derived data from the amplitude and/orphase data can provide improved correspondence to a health parameter,such as blood glucose level, the particular model that provides adesired level of correspondence (e.g., that meets a predeterminedaccuracy) may need to be learned in response to a specific set ofoperating conditions. Thus, in an embodiment, a learning process (e.g.,machine learning) is implemented to identify and train a model thatprovides an acceptable correspondence to a health parameter such asblood glucose level.

FIG. 27 illustrates a system 2700 and process for machine learning thatcan be used to identify and train a model that reflects correlationsbetween raw data, derived data, and control data. For example, themachine learning process may be used to identify certain statistics(e.g., standard deviation of amplitude and/or phase over time) that canbe used to improve the correspondence of determined values to actualhealth parameters (such as blood glucose levels) in a person. Themachine learning process can also be used to train a model with trainingdata so that the trained model can accurately and reliably determinevalues for health parameters such as blood glucose level, bloodpressure, and/or heart rate in monitoring devices that are deployed inthe field. With reference to FIG. 27, the system 2700 includes a sensorsystem 2710, a machine learning engine 2760, a trained model database2762, and a control element 2764.

In an embodiment, the sensor system 2710 is similar to or the same asthe sensor system described above. For example, the sensor system isconfigured to implement stepped frequency scanning in the 2-6 GHz and/or122-126 GHz frequency range using two transmit antennas and four receiveantennas. The sensor system generates and outputs raw data to themachine learning engine that can be accumulated and used as describedbelow.

In an embodiment, the control element 2764 is configured to provide acontrol sample to the sensor system 2710. For example, the controlelement includes a sample material 2766 (e.g., a fluid) that has a knownblood glucose level that is subjected to the sensor system.Additionally, in an embodiment, the control element is configured toprovide control data to the machine learning engine that corresponds tothe sample material. For example, the control element may include asample material that has a known blood glucose level that changes as afunction of time and the change in blood glucose level as a function oftime (e.g., Z(t) mg/dL) is provided to the machine learning engine 2760in a manner in which the raw data from the sensor system 2710 and thecontrol data can be time matched (e.g., synchronized). In anotherembodiment, the control element 2764 includes a sample material thatincludes a static parameter, e.g., a static blood glucose level inmg/dL, and the static parameter is manually provided to the machinelearning engine 2760 as the control data. For example, a particularsample is provided within range of RF energy 2770 that is transmittedfrom the sensor system (e.g., within a few millimeters), theconcentration of the sample is provided to the machine learning engine(e.g., manually entered), and the sensor system accumulates digital datathat corresponds to the received RF energy (including a reflectedportion of the transmitted RF energy) and that is correlated to thesample. In one embodiment, the sample material is provided in acontainer such as a vial and in another embodiment, the control elementincludes a person that is simultaneously being monitored by the sensorsystem (e.g., for the purposes of machine learning) and by a second,trusted, control monitoring system. For example, the control elementincludes a person who's blood glucose level, blood pressure, and/orheart rate is being monitored by a known (e.g., clinically accepted)blood glucose level, blood pressure, and/or heart rate monitor while theperson is simultaneously being monitored by the sensor system. The bloodglucose level, blood pressure, and/or heart rate information from theknown blood glucose level, blood pressure, and/or heart rate monitor isprovided to the machine learning engine as control data.

In an embodiment, the machine learning engine 2760 is configured toprocess the raw data received from the sensor system 2710, e.g., as rawdata records, and the control data received from the control element2764 to learn a correlation, or correlations, that provides acceptablecorrespondence to a health parameter such as blood glucose levels. Forexample, the machine learning engine is configured to receive raw datafrom the sensor system, to derive data from the raw data such asstatistical data, and to compare the derived data (and likely at leastsome portion of the corresponding raw data) to the control data to learna correlation, or correlations, that provides acceptable correspondencebetween a determined value of a health parameter and a controlled, orknown value, of the health parameter. In an embodiment, the machinelearning engine is configured to derive statistics from the raw datasuch as a standard deviation, a moving average, and a moving mean. Forexample, the machine learning engine may derive the standard deviationof the amplitude and/or phase of the received RF energy and thencorrelate the derived statistic(s) and the raw data to the control datato find a correlation that provides an acceptable correspondence betweenthe raw data, the derived data, and the actual value of the healthparameter as provided in the control data. In an embodiment,correspondence between the raw data, the derived data, and the actualvalues of the health parameter in a control sample is expressed in termsof a correspondence threshold, which is indicative of, for example, thecorrespondence between values of a health parameter generated inresponse to the raw data, the derived data, and actual values of thehealth parameter in a control sample. For example, a correspondence isexpressed as a percentage of correspondence to the actual value of thecontrol sample such that a generated concentration value of a bloodglucose level of 135 mg/dL and a value of a control sample at 140 mg/dLhas a correspondence of 135/140=96.4%. In an embodiment, acorrespondence threshold can be set to accept only those correlationsthat produce correspondence that meets a desired correspondencethreshold. In an embodiment, a correspondence threshold of a generatedvalue to the value of a control sample of within ±10% of the controlsample is acceptable correspondence. In another embodiment, acorrespondence threshold of within ±10% of the control sample in 95% ofthe measurements is acceptable correspondence.

FIG. 28 is an example of a process flow diagram of a method forimplementing machine learning using, for example, the system describedabove with reference to FIG. 27 to select a correlation (e.g., a modelor algorithm) that provides acceptable correspondence between values ofa health parameter generated in response to the raw data, the deriveddata, and actual values of the health parameter in the control samples.At block 2802, raw data is obtained from the sensor system. At block2804, the raw data is correlated to known control data, such as knownblood glucose levels. At decision point 2806, it is determined whether acorrelation between the raw data and the control data is acceptable,e.g., whether the correspondence is within an acceptable threshold. Ifit is determined that there is an acceptable correspondence, then theprocess proceeds to block 2808, where the correlation (e.g., a model oralgorithm) is saved and then the initial learning process is ended. Ifat decision point 2806 it is determined that there is not an acceptablecorrespondence between the raw data and the control data (e.g., thecorrespondence is not within an acceptable threshold), then the processproceeds to block 2810. At block 2810, additional data is derived fromthe raw data. For example, the machine learning engine may derive astatistic or statistics from the raw data such as a standard deviation,a moving average, and a moving mean. For example, the machine learningengine may derive the standard deviation of the amplitude and/or phaseof the received RF energy. At decision point 2812, it is determinedwhether a correlation between the raw data, the derived data, and thecontrol data is acceptable (e.g., the correspondence is within anacceptable threshold). If it is determined that there is an acceptablecorrespondence between the raw data, the derived data, and the controldata, then the process proceeds to block 2814, where the correlation(e.g., a model or algorithm) is saved and then the initial learningprocess is ended. If at decision point 2812 it is determined that thereis not an acceptable correspondence between the raw data, the deriveddata, and the control data (e.g., the correspondence is not within anacceptable threshold), then the process returns to block 2810. At block2810, additional data is derived from the raw data and/or from thederived data. For example, a different statistic, or statistics, isderived from the raw data and/or from the previously derived data. In anembodiment, the exploration of correlations between the raw data, thederived data, and the control data is an iterative process thatconverges on a correlation, or correlations, which provides acceptablecorrespondence between the raw data, the derived data, and the controldata. In an embodiment, the machine learning process can be repeatedlyused to continue to search for correlations that may improve thecorrespondence between the raw data, the derived data, and the controldata to improve the accuracy of health parameter monitoring.

In an embodiment, the above-described process is used for algorithmselection and/or model building as is done in the field of machinelearning. In an embodiment, algorithm selection and/or model buildinginvolves supervised learning to recognize patterns in the data (e.g.,the raw data, the derived data, and/or the control data). In anembodiment, the algorithm selection process may involve utilizingregularized regression algorithms (e.g, Lasso Regression, RidgeRegression, Elastic-Net), decision tree algorithms, and/or treeensembles (random forests, boosted trees).

In an embodiment, acceptable correlations that are learned by themachine learning engine are trained by the machine learning engine toproduce a trained model, or trained models, that can be deployed in thefield to monitor a health parameter of a person. Referring back to FIG.27, a model that is trained by the machine learning engine 2760 is heldin the trained model database 2762. In an embodiment, the trained modeldatabase may store multiple models that have been found to provideacceptable correspondence between generated values of a health parameterand the actual values of the health parameter as provided in the controldata. Additionally, the trained model database 2762 may provide rules onhow to apply the model in deployed sensor systems. For example,different models may apply to different deployment conditions, e.g.,depending on the location of the RF front-end relative to a bloodvessel, environmental conditions, etc.

In an embodiment, operation of the system 2700 shown in FIG. 27 togenerate training data and to train a model using the training datainvolves providing a control sample in the control element 2764 and thenoperating the sensor system 2700 to implement stepped frequency scanningover a desired frequency range that is within, for example, the 2-6 GHzand/or 122-126 GHz frequency range. For example, control datacorresponding to the control sample 2766 is provided to the machinelearning engine 2760 and raw data generated from the sensor system 2710is provided to the machine learning engine. The machine learning enginegenerates training data by combining the control data with the steppedfrequency scanning data in a time synchronous manner. The machinelearning engine processes the training data to train a model, or models,which provides an acceptable correspondence between generated values ofa health parameter and the control data. The model, or models, is storedin the trained model database 2762, which can then be applied to asystem 2700 that is deployed in the field to monitor a health parameterof a person. In an embodiment, the sensor system is exposed to multipledifferent samples under multiple different operating conditions togenerate a rich set of training data.

In an embodiment, the goal of the training process is to produce atrained model that provides a high level of accuracy and reliability inmonitoring a health parameter in a person over a wide set of parameterranges and operational and/or environmental conditions. For example, thecorrespondence of a model during training can be expressed in terms of acorrespondence threshold, which is indicative of, for example, thecorrespondence between values of a health parameter generated inresponse to the raw data, the derived data, and actual values of thehealth parameter in a control sample. For example, a correspondence isexpressed as a percentage of correspondence to the actual value of thecontrol sample such that a generated concentration value of a bloodglucose level of 135 mg/dL and a value of a control sample at 140 mg/dLhas a correspondence of 135/140=96.4%. In an embodiment, acorrespondence threshold can be set for a trained model so that thetrained model produces correspondence that meets a desiredcorrespondence threshold. In an embodiment, a correspondence thresholdof a generated value to the value of a control sample of within ±10% ofthe control sample is acceptable correspondence for a trained model. Inanother embodiment, a correspondence threshold of within ±10% of thecontrol sample in 95% of the measurements is acceptable correspondencefor a trained model.

In an embodiment, the correspondence between the raw and/or derived dataand the control data may change in response to different factorsincluding, for example, over different blood glucose levels, differentmonitoring locations, different environmental conditions, etc. Thus, insome embodiments, the trained model database 2762 may include multipledifferent trained models that are applicable to certain conditions.Additionally, the trained model database may evolve over time as moreinformation is gathered and/or as different correlations are discovered.

As described above, the model training process utilizes raw data (e.g.,in the form of raw data records) as inputs into the machine learningengine. FIG. 29 is an example of a table of a raw data record (e.g.,digital data) generated during stepped frequency scanning that is usedto generate the training data. The raw data record includes time t1, aknown blood glucose level (e.g., a control sample with a knownconcentration of glucose in mg/dL, Z mg/dL) at the time t1, TX/RXfrequency at the time t1, RX1 amplitude/phase, RX2 amplitude/phase, RX3amplitude/phase, and RX4 amplitude/phase at the time t1. In the exampleof FIG. 29, the raw data record includes the glucose level of thecontrol sample at the same time the amplitude and phase of the RF energywas received by the sensor system, thus, the control data is combinedwith the stepped frequency scanning data in a time synchronous manner.In addition, the raw data records that are used to generate the trainingdata may include some or all of the parameters identified in FIGS. 23and 24. For example, the raw data records and the corresponding trainingdata may include other variable and/or fixed parameters that correspondto the stepped frequency scanning operation to provide a rich set ofparameters from which to generate the training data.

In a stepped frequency scanning operation, multiple raw data records aregenerated as the sensor system scans across a frequency range. FIGS.30A-30D are tables of at least portions of raw data records that aregenerated during a learning process that spans the time of t1-tn, wheren corresponds to the number (e.g., an integer of 2 or greater) of timeintervals, T, in the stepped frequency scanning. Each of the raw datarecords includes control data (e.g., known glucose level, Z mg/dL) thatis combined with stepped frequency scanning data in a time synchronousmanner.

With reference to FIG. 30A, at time, t1, the raw data record includesthe time, t1, a known blood glucose level (e.g., Z1 in mg/dL) at timet1, a TX/RX frequency (e.g., X GHz) at time t1, RX1 amplitude/phase attime t1 (ampl1-t1/ph1-t1), RX2 amplitude/phase at time t1(ampl2-t1/ph2-t1), RX3 amplitude/phase at time t1 (ampl3-t1/ph3-t1), andRX4 amplitude/phase at time t1 (ampl4-t1/ph4-t1). In the steppedfrequency scanning, at the next time, t2, the frequency is changed byone step size, e.g., incremented by Δf. In an embodiment, the steppedfrequency scanning operation generates 200 raw data records per second,e.g., a sample rate of 200 samples/second. With reference to FIG. 30B,at time, t2, the raw data record includes the time, t2, a known bloodglucose level (e.g., Z2 in mg/dL) at time t2, a TX/RX frequency (e.g.,X+Δf GHz) at time t2, RX1 amplitude/phase at time t2 (ampl1-t2/ph1-t2),RX2 amplitude/phase at time t2 (ampl2-t2/ph2-t2), RX3 amplitude/phase attime t2 (ampl3-t2/ph3-t2), and RX4 amplitude/phase at time t2(ampl4-t2/ph4-t2). With reference to FIG. 30C, at time, t3, the raw datarecord includes the time, t3, a known blood glucose level (e.g., Z3 inmg/dL) at time t3, a TX/RX frequency (e.g., X+2Δf GHz) at time t3, RX1amplitude/phase at time t3 (ampl1-t3/ph1-t3), RX2 amplitude/phase attime t3 (ampl2-t3/ph2-t3), RX3 amplitude/phase at time t3(ampl3-t3/ph3-t3), and RX4 amplitude/phase at time t3 (ampl4-t3/ph4-t3).With reference to FIG. 30D, at time, tn, the raw data record includesthe time, tn, a known blood glucose level (e.g., Zn in mg/dL) at timetn, a TX/RX frequency (e.g., X+(n−1)Δf GHz) at time tn, RX1amplitude/phase at time tn (ampl1-tn/ph1-tn), RX2 amplitude/phase attime tn (ampl2-tn/ph2-tn), RX3 amplitude/phase at time tn(ampl3-tn/ph3-tn), and RX4 amplitude/phase (ampl4-tn/ph4-tn) at time tn.

As illustrated above, raw data is collected on a per-antenna basis forthe amplitude and/or phase of the received RF energy. Raw data collectedon a per-antenna basis for amplitude and phase for the example of FIGS.30A-30D may include:

ampl1: ampl1-t1, ampl1-t2, ampl1-t3, . . . , ampl1-tn;

ampl2: ampl2-t1, ampl2-t2, ampl2-t3, . . . , ampl2-tn;

ampl3: ampl3-t1, ampl3-t2, ampl3-t3, . . . , ampl3-tn;

ampl4; ampl4-t1, ampl4-t2, ampl4-t3, . . . , ampl4-tn;

ph1: ph1-t1, ph1-t2, ph1-t3, . . . , ph1-tn;

ph2: ph2-t1, ph2-t2, ph2-t3, . . . , ph2-tn;

ph3: ph3-t1, ph3-t2, ph3-t3, . . . , ph3-tn); and

ph4: ph4-t1, ph4-t2, ph4-t3, . . . , ph4-tn).

In the example of FIGS. 30A-30D, the standard deviation may becalculated on a per-antenna basis for the amplitude and phase and is afunction of the following raw data elements:

σ(ampl1)=f(ampl1-t1+ampl1-t2+ampl1-t3+ . . . +ampl1-tn);

σ(ampl2)=f(ampl2-t1+ampl2-t2+ampl2-t3+ . . . +ampl2-tn);

σ(ampl3)=f(ampl3-t1+ampl3-t2+ampl3-t3+ . . . +ampl3-tn);

σ(ampl4)=f(ampl4-t1+ampl4-t2+ampl4-t3+ . . . +ampl4-tn);

σ(ph1)=f(ph1-t1+ph1-t2+ph1-t3+ . . . +ph1-tn);

σ(ph2)=f(ph2-t1+ph2-t2+ph2-t3+ . . . +ph2-tn);

σ(ph3)=f(ph3-t1+ph3-t2+ph3-t3+ . . . +ph3-tn); and

σ(ph4)=f(ph4-t1+ph4-t2+ph4-t3+ . . . +ph4-tn).

In an embodiment, data is derived on a per-antenna basis. In otherembodiments, data such as statistics can be derived from datacorresponding to different combinations of antennas.

Raw data records collected over time can be used as described above tolearn correlations (e.g., a model or algorithm) between the raw data,derived data, and the control data and to train a model. In anembodiment, a rich set of training data is collected and processed totrain a model that can provide accurate and reliable measurements of ahealth parameter such as blood glucose level, blood pressure, and/orheart rate. In an embodiment, the raw data including amplitude and phaseand the derived data including the standard deviation of the amplitudehas been found to correspond well to the health parameter of bloodglucose level.

Once correlations between the raw data, the derived data, and thecontrol data have been learned and a model has been trained, a sensorsystem can be deployed into the field for use in monitoring a healthparameter of a person, such as the blood glucose level. FIG. 31illustrates a system 3100 for health parameter monitoring that utilizesa sensor system similar to or the same as the sensor system describedabove. With reference to FIG. 31, the system includes a sensor system3110, a health parameter determination engine 3180, and a trained modeldatabase 3182.

In an embodiment, the sensor system 3110 is similar to or the same asthe sensor system described above. For example, the sensor system isconfigured to implement stepped frequency scanning in the 2-6 GHz and/or122-126 GHz frequency range using two transmit antennas and four receiveantennas. The sensor system generates and outputs raw data to the healthparameter determination engine 3180 that can be accumulated and used togenerate and output a value that corresponds to a health parameter.

A model (or models) that is trained by the machine learning engine asdescribed above is held in the trained model database 3182. In anembodiment, the trained model database may store multiple models thathave been trained to provide acceptable correspondence between agenerated value of a health parameter and the actual value of the healthparameter as provided in the control data. Additionally, the trainedmodel database may provide rules on how to apply trained models indeployed sensor systems. In an embodiment, the trained model databaseincludes memory for storing a trained model, or models. The memory mayinclude, for example, RAM, SRAM, and/or SSD.

In an embodiment, the health parameter determination engine 3180 isconfigured to generate an output that corresponds to a health parameterin response to the raw data received from the sensor system 3110,derived data, and using a trained model that is stored in the trainedmodel database 3182. For example, the health parameter determinationengine 3180 outputs a value that indicates a blood glucose level inmg/dL or some other indication of the blood glucose level. In otherembodiments, the health parameter determination engine may output avalue that is an indication of a person's heart rate (e.g., in beats perminute) and/or an indication of a person's blood pressure (e.g., inmillimeters of mercury, mmHg). In other embodiments, the “values” outputby the health parameter determination engine may correspond to a healthparameter in other ways. For example, the output value may indicate avalue such as “high,” “medium,” “low” with respect to a health parameter(e.g., a high blood glucose level, a medium blood glucose level, or alow blood glucose level relative to a blood glucose scale), the outputvalue may indicate a color, such as green, yellow, or red that indicatesa health parameter, or the output value, may indicate a range of values,such as 130-140 mg/dL blood glucose, 70-80 beats per minute, or 110-120mmHg blood pressure. In an embodiment, the health parameterdetermination engine recognizes patterns in the raw and/or derived dataand applies the recognized patterns to the trained model to generate anoutput that corresponds to a health parameter in a person. The healthparameter determination engine may be implemented by a digitalprocessor, such as a CPU or MCU, in conjunction with computer readableinstructions that executed by the digital processor.

In an embodiment, operation of the system 3100 shown in FIG. 31 involvesbringing a portion of a person's anatomy 3186 (such as a wrist, arm, orear area) into close proximity to the sensor system 3110 (or bringingthe sensor system into close proximity to the portion of a person'sanatomy) and operating the sensor system to implement stepped frequencyscanning over a frequency range, e.g., in the range of 122-126 GHz suchthat transmitted RF energy 3170 penetrates below the surface of theperson's skin. Raw data generated from implementing the steppedfrequency scanning is output from the sensor system and received at thehealth parameter determination engine 3180. The health parameterdetermination engine processes the raw data in conjunction with at leastone trained model from the trained model database 3182 to generate avalue that corresponds to a health parameter of the person, e.g., avalue that corresponds to the blood glucose level of the person. In anembodiment, the value that corresponds to the health parameter isoutput, for example, as a graphical indication of the blood glucoselevel. In an embodiment, the generated value may be stored in a healthparameter database for subsequent access.

In an embodiment, the system 3100 depicted in FIG. 31 is implemented ina device such as a smartwatch or smartphone. In other embodiments, someportion of the system (e.g., the RF front-end) is implemented in adevice, such as a dongle, a patch, a smartphone case, or some otherdevice and the health parameter determination engine and the trainedmodel correlations database is implemented in a nearby device such as asmartphone. For example, in one embodiment, the sensor system isembodied in a device that attaches near the ear of a person and raw datais communicated via a wireless connection to a device such as asmartphone that processes the raw data to generate a value thatcorresponds to the blood glucose level of the person.

FIG. 32 is a process flow diagram of a method for monitoring a healthparameter in a person. At block 3202, radio waves are transmitted belowthe skin surface of a person and across a range of stepped frequencies.At block 3204, radio waves are received on a two-dimensional array ofreceive antennas, the received radio waves including a reflected portionof the transmitted radio waves across the range of stepped frequencies.At block 3206, data that corresponds to the received radio waves isgenerated, wherein the data includes amplitude and phase data. At block3208, a value that is indicative of a health parameter in the person isdetermined in response to the amplitude and phase data.

FIG. 33 is a process flow diagram of another method for monitoring ahealth parameter in a person. At block 3302, radio waves are transmittedbelow the skin surface of a person and across a range of steppedfrequencies. At block 3304, radio waves are received on atwo-dimensional array of receive antennas, the received radio wavesincluding a reflected portion of the transmitted radio waves across therange of stepped frequencies. At block 3306, data that corresponds tothe received radio waves is generated, wherein the data includesamplitude and phase data. At block 3308, data is derived from at leastone of the amplitude and phase data. At block 3310, a value that isindicative of a health parameter in the person is determined in responseto the derived data.

FIG. 34 is a process flow diagram of a method for training a model foruse in monitoring a health parameter in a person. At block 3402, controldata that corresponds to a control element is received, wherein thecontrol data corresponds to a health parameter of a person. At block3404, stepped frequency scanning data that corresponds to radio wavesthat have reflected from the control element is received, wherein thestepped frequency scanning data includes frequency and correspondingamplitude and phase data over a range of frequencies. At block 3406,training data is generated by combining the control data with thestepped frequency scanning data in a time synchronous manner. At block3408, a model is trained using the training data to produce a trainedmodel, wherein the trained model correlates stepped frequency scanningdata to values that are indicative of a health parameter of a person.

In order to achieve accurate and reliable correspondence between sensormeasurements and actual values of the monitored health parameter usingan RF-based sensor system, such as the above described RF-based sensorsystem, it is desirable to have the antenna array in contact with orclose to the skin (e.g., within 5 mm) aligned with a vein that is to besensed or monitored. For example, it is desirable to have the veinaligned with the two-dimensional array of antennas of the sensor system,e.g., laterally aligned with the two-dimensional array of receiveantennas. FIG. 35A illustrates an antenna array of the sensor system3522 as described above with reference to FIGS. 5-8D and a vein 3516aligned between the TX antennas 3544 and RX antennas 3546 of the antennaarray of the sensor system. Specifically, in the example of FIG. 35A,the antennas of the sensor system are positioned relative to the veinsuch that the vein is centered between the left side antennas (RX, TX,and RX) and the right side antennas (RX, TX, and RX). FIGS. 35B and 35Cillustrate examples in which the antenna array of the sensor system isnot aligned with the vein along a centerline 3523 between the antennasof the sensor system, but the alignment relative to the vein is eitherslightly left of the centerline between the antennas (FIG. 35B) orslightly right of the centerline between the antennas (FIG. 35C). Insome embodiments, an alignment slightly off of the centerline may stillprovide acceptable accuracy and reliability of measurements. FIGS. 35Dand 35E illustrate examples in which the antenna array of the sensorsystem is not aligned with the vein along the centerline of the sensorsystem. In particular, FIG. 35D illustrates a case in which the antennaarray of the sensor system is fully outside of the footprint of, and tothe left of, the sensor system and FIG. 35E illustrates a case in whichthe antenna array of the sensor system is fully outside of the footprintof, and to the right of, the sensor system.

As shown in FIGS. 35A-35E, the two-dimensional antenna array 3544 and3546 of the sensor system 3522 can be in various different positionsrelative to the vein 3516 to be monitored, e.g., lateral positionsrelative to the plan views of FIGS. 35A-35E. In an embodiment, a measureof alignment between the antenna array and a vein to be monitoredinvolves comparing an actual alignment of an antenna array to an idealalignment of an antenna array, e.g., an ideal alignment in which thevein is aligned along the centerline 3523 between the antennas as shownin FIG. 35A. In an embodiment, a measure of alignment involvesdetermining a distance (e.g., lateral distance relative to the planviews of FIGS. 35A-35E) of the vein from the centerline between theantennas. For example, the distance may be determined as a lateraldistance of the vein from the centerline between the antennas at morethan one location along the centerline, e.g., as viewed from a top planview as shown in FIGS. 35A-35E. In an embodiment, the distance ismeasured as the average distance of the vein from the centerline betweenthe antennas as determined at a point between the two upper receiveantennas and at a point between the two lower antennas although othertechniques for obtaining a measure of alignment are possible.

In an embodiment, an antenna array is considered aligned with a veinwhen the vein is within a predefined threshold distance from thecenterline between the two-dimensional array of receive antennas.Examples of the predefined threshold may be for example within 10% ofthe linear distance between a particular receive antenna and thecenterline between the two-dimensional array of receive antennas. In anembodiment, the location of an ideally aligned vein relative to anantenna array can be predefined by experimentation and or by geometricanalysis. Additionally, alignment of a vein relative to an antenna arraymay vary depending on the spatial configuration of the antennas. In anembodiment, a desired alignment between a vein and an antenna array isan alignment that results in reflections of radio waves from the veinthat have a higher amplitude than reflections of other alignmentsbetween the vein and the antenna array.

Although it is desirable to have the antenna array of the sensor system(e.g., including the two-dimensional array of receive antennas) alignedwith a vein of the person that is to be monitored (e.g., in terms ofboth lateral alignment and separation distance between the antenna arrayand the skin of the person to be monitored), it has been found thataligning a sensor system (e.g., including the two-dimensional array ofreceive antennas) with a vein of a person that is to be monitored andmaintaining the alignment during health parameter monitoring is not atrivial endeavor.

Various techniques for aligning a health monitoring device, inparticular, an antenna array of an RF-based health monitoring device,with an object, which may include a vein of a person to be monitoredand/or another alignment element, are described herein. Some of thetechniques utilize digital data generated by an RF front-end toimplement alignment while other techniques utilize a physical feature,or features, of a health monitoring device or a health monitoring systemto implement alignment. Additionally, alignment features may beimplemented in various different components of a health monitoringdevice or a health monitoring system depending on the configurationand/or form factor of the health monitoring device or the healthmonitoring system.

In at least some of the examples described below, the alignmenttechnique is an RF-based alignment technique at least because alignmentdeterminations are made in response to radio waves that are received bythe sensor system. In an embodiment, alignment features are generated inresponse to a signal that is indicative of an alignment that isdetermined based on the received radio waves. For example, an alignmentprocess may involve transmitting radio waves below the skin surface of aperson, receiving radio waves on a two-dimensional array of receiveantennas of an antenna array, the received radio waves including areflected portion of the transmitted radio waves, determining analignment of the antenna array relative to a vein in the person inresponse to the received radio waves, and outputting a signal that isindicative of the determined alignment of the antenna array relative tothe vein. In an embodiment, the signal includes a visual indicator ofalignment. In an embodiment, the process further involves displaying avisual indicator of alignment on a display of a health parametermonitoring system in response to the signal. In an embodiment, thevisual indicator of alignment includes an alignment feature and agraphical representation of a detected vein. In an embodiment, thevisual indicator of alignment includes an alignment feature on a displayof a health parameter monitoring system. In an embodiment, the visualindicator of alignment includes an alignment feature that is stationaryon a display and a visual representation of a detected vein that movesin response to movement of the antenna array relative to the detectedvein. In an embodiment, the process involves emitting light from a lightsource of a health parameter monitoring system in response to the outputsignal as an indicator of alignment of the antenna array relative to thevein. In an embodiment, the process further involves generating an audiosignal that is indicative of alignment of the antenna array relative tothe vein in response to the output signal. In an embodiment, the processfurther involves generating a tactile signal that is indicative ofalignment of the antenna array relative to the vein in response to theoutput signal. In an embodiment, the method further involves displayinga visual indicator of alignment of the antenna array relative to thevein on a display of a smartwatch in response to the output signal. Inan embodiment, the process further involves displaying a visualindicator of alignment of the antenna array relative to the vein on adisplay of a smartphone in response to the output signal. In anembodiment, the process further involves generating a visual indicatorof alignment of the antenna array relative to the vein in response tothe output signal when it is determined that the antenna array isaligned with the vein. In an embodiment, the antenna array is alignedwith the vein when an equal number of receive antennas are on eitherside of the vein. In an embodiment, the process further involvesgenerating an audible indicator of alignment in response to the outputsignal when it is determined that the antenna array is aligned with thevein. In an embodiment, the method further involves generating a tactileindicator of alignment in response to the output signal when it isdetermined that the antenna array is aligned with the vein. In anembodiment, the transmitting and receiving are implemented in aremovable smartphone case and the determining and outputting areimplemented in a smartphone that is connected to the removablesmartphone case. In an embodiment, the process further involvesdisplaying a visual indicator of alignment on a display of thesmartphone in response to the output signal. In an embodiment, thetransmitting, the receiving, the determining, and the outputting areimplemented in a removable smartphone case. In an embodiment, theprocess further involves generating a visual indicator of alignment onthe removable smartphone case in response to the output signal.

In an embodiment, the sensor system described above is implemented in asmartwatch and the smartwatch, including the sensor system is configuredto implement RF-based alignment. An example of RF-based alignment is nowdescribed with reference to FIGS. 36A-36E. With reference to FIG. 36A,the smartwatch 3600 is configured to display an alignment feature 3620on the display device (also referred to simply as the display) of thesmartwatch. In the example of FIG. 36A, the alignment feature includestwo horizontal lines that run parallel to each other across the display(e.g., from left side to the right side or vice versa) to form an“alignment channel.” In an embodiment, the alignment channel isdisplayed as a graphical element on a graphical user interface of thesmartwatch. In the example of FIG. 36A, the alignment channel is theonly graphical element on the display although other information may beincluded on the display.

When the smartwatch 3600 is operational and worn on the wrist of aperson, an alignment system of the smartwatch uses the RF-based sensorsystem to detect the location of a vein in the wrist relative to theantenna array of the sensor system. For example, the location of a veinin the wrist relative to the antenna array of the sensor system can bedetermined by a processor of the smartwatch using Doppler effectprocessing as described above with reference to FIG. 19. Othertechniques may also be used to determine the location of a vein relativeto the antenna array of the sensor system including, for example,beamforming techniques that involve isolating radio waves that arereflected from a specific location (e.g., onto a specific blood vessel)to provide a high-quality signal that can be used to determine thelocation of a vein relative to the antenna array (e.g., relative to thetwo-dimensional array of receive antennas). The location of the veinrelative to the antenna array of the sensor system, also referred to ingeneral as “the alignment,” can be graphically represented by a visualindicator of alignment. In an embodiment, it is assumed that theseparation distance between the smartwatch and the skin is known (e.g.,no separation or a separation within a very narrow range, e.g., in therange of 0-10 mm, or in the range of 0-5 mm) and the alignment to bemonitored and adjusted is primarily lateral alignment, e.g., laterallyfrom a plan view as shown in FIGS. 35A-35E. FIG. 36B depicts an exampleof the alignment channel 3624 (as shown in FIG. 36A) and a graphicalrepresentation of the detected vein 3626 displayed relative to thealignment channel. As shown in FIG. 36B, the graphical representation ofthe vein is not aligned with the alignment channel, at least because nopart of the visual representation of the vein falls within the alignmentchannel. Thus, FIG. 36B illustrates an example in which the antennaarray of the sensor system and the monitored vein are not satisfactorilyaligned with each other. In order to align the antenna array of thesensor system with the monitored vein, the display of the alignmentchannel relative to the graphical representation of the vein on thegraphical user interface intuitively encourages a person (e.g., theperson wearing the smartwatch) to manually move or adjust the positionof the smartwatch on the wrist. For example, the wearer of thesmartwatch is intuitively encouraged to move the smartwatch “upwards” toalign the graphical representation of the vein with the alignmentchannel. FIG. 36C illustrates the upward movement of the smartwatch asindicated by the upward pointing arrows. FIG. 36C also illustrates thatas the smartwatch is moved upwards, the graphical representation of thevein moves downward towards the alignment channel while the alignmentfeature remains stationary on the display. Although the graphicalrepresentation of the vein 3626 has moved closer to the alignmentchannel 3624, and indeed is partially within the bounds of the alignmentchannel, it is clear from the structure of the alignment channel andfrom the position of the graphical representation of the vein relativeto the alignment channel, that a better alignment between the graphicalrepresentation of the vein and the alignment channel can be achieved.Thus, the wearer of the smartwatch is intuitively encouraged to continueto move and/or adjust the position of the smartwatch on the wrist.

FIG. 36D illustrates further upward movement of the smartwatch 3600 asindicated by the upward pointing arrows. FIG. 36D also illustrates thatas the smartwatch is moved upwards, the graphical representation of thevein 3626 moves further downwards and into alignment with the alignmentchannel 3624. As depicted in FIG. 36E, the graphical representation ofthe vein is now entirely within the bounds of the alignment channel,which graphically indicates alignment between the graphicalrepresentation of the vein and the alignment channel, which in turncorrelates to alignment between the antenna array of the sensor system(e.g., the two-dimensional array of receive antennas) and the monitoredvein.

As depicted in FIG. 36E, once alignment between the antenna array of thesensor system and the monitored vein is achieved, an outputrepresentative of the alignment can be displayed. For example, theboundaries of the alignment channel visibly change (e.g., thicken up,brighten up, and/or change color) and an alignment message (e.g.,“Aligned!”) is displayed.

An example of the alignment process described with reference to FIGS.36A-36E is further illustrated in FIGS. 37A and 37B. FIG. 37A depicts asmartwatch 3700 that is worn on the left wrist 3730 of a person. In theexample of FIG. 37A, the graphical representation of the vein is notaligned with the alignment channel, which as described with reference toFIG. 36A, indicates that the antenna array of the sensor system is notaligned with the monitored vein in the wrist of the person wearing thesmartwatch. For example, the antenna array is not laterally aligned withthe vein, where lateral alignment is defined relative to a plan view asshown in FIGS. 35A-35E. FIG. 37B illustrates the position of thesmartwatch being manually moved and/or adjusted by the right hand 3731of the person wearing the smartwatch. As indicated by the upwardpointing arrows, the smartwatch is moved upwards until the graphicalrepresentation of the vein is entirely within the bounds of thealignment channel. FIG. 37B also depicts the alignment message (e.g.,“Aligned!”) as depicted in FIG. 36E.

In the embodiments described with reference to FIGS. 36A-37B, theposition of the vein relative to the alignment channel is determined inresponse to radio waves that are received by the sensor system. Forexample, the graphics of the graphical user interface are generated inresponse to digital data that is generated in response to reflectedradio waves. For example, the graphics in the graphical user interfaceare driven by digital data from the RF sensor system and Doppler effectprocessing as described with reference to FIG. 19.

In an embodiment, the alignment system is configured such that thealignment indicator (e.g., an alignment channel 3724) and the graphicalrepresentation of vein 3726 are oriented to correspond to the actualposition of the monitored vein to make it appear as if the person cansee the monitored vein. For example, FIG. 37C depicts the actuallocation of a vein 3734 running through a portion of the arm and handand a graphical representation of the vein 3726 on the graphical userinterface of the smartwatch in which the boundaries of the graphicalrepresentation of the vein match the boundaries of the actual vein atthe location of the smartwatch. Such a configuration of the graphicalrepresentation of the vein helps to create an alignment feature thatpromotes intuitive alignment adjustments. In an embodiment, thealignment features can be adapted on-the-fly to the orientation of theantenna array relative to the vein. In an embodiment, the graphicalrepresentation of the vein may include other graphical features that,for example, represent blood flow, the direction of blood flow, thepulsing of the blood flow, and/or the color of the blood. In anembodiment, the color of the graphical representation of the vein orsome other feature of the graphical representation of the vein (e.g.,the texture) may be used to represent a value of a health parameter,such as a blood glucose level, a pulse rate, or blood pressure.

Other, less intuitive configurations of an alignment feature, orfeatures are possible. FIGS. 38A and 38B, show an example of a lessintuitive configuration of an alignment channel 3825 and a graphicalrepresentation of a vein 3827. In the example of FIGS. 38A and 38B, upand down movement of the smartwatch 3800 on the wrist 3830 causes leftand right movement of the graphical representation of the vein, whichmay be less intuitive and may lead to confusion of the user. Thus, theconfiguration as described with reference to FIGS. 36A-36E and FIGS. 37Aand 37B provides an intuitive user interface that may have advantagesover other possible configurations.

Although an example of an alignment feature and corresponding alignmenttechnique is described with reference to FIGS. 36A-36E and FIGS. 37A and37B, other RF-based alignment features can be implemented and displayedon the display of a health monitoring device such as a smartphone. FIGS.39A and 39B depict an example of another type of RF-based alignmentfeature that can be used to align an antenna array of a sensor systemwith a monitored vein. With reference to FIG. 39A, the alignment featureis simply an arrow 3928 that encourages the user to move and/or adjustthe position of the smartwatch 3900 on the wrist 3930 in the directionof the arrow. FIG. 39B illustrates the position of the smartwatch beingmanually moved and/or adjusted on the wrist in the direction of thearrow by the right hand 3931 of the person wearing the smartwatch. Asindicated by the upward pointing arrows, the smartwatch is moved upwardsuntil alignment is achieved and, for example, an alignment message(e.g., “Aligned!”) is displayed.

Although some examples of RF-based alignment features are provided,other configurations of an RF-based alignment feature or features arepossible. Additionally, in an embodiment, an output signal generated inresponse to the radio waves may be used to generate an indicator ofalignment that is an audio signal (e.g., a sound that encouragesalignment) or a tactile signal (e.g., a vibration that encouragesalignment).

In the examples described above with reference to FIGS. 36A-39B, thesensor system is integrated into a smartwatch. In other embodiments, thesensor system can be integrated into other types of devices and/orsystems, including, for example, a smartphone, a removable smartphonecase, and a strap or band for a watch, a ring (e.g., to be worn on afinger), or another device.

FIGS. 40A and 40B depict an embodiment of a smartphone 4000 thatincludes a sensor system as described above integrated into thesmartphone. For example, the sensor system includes an RF IC device 4010as described above with reference to FIGS. 5-8D integrated into thesmartphone. In the embodiment depicted in FIG. 40B, the sensor system isintegrated into the smartphone near the backside 4041 of the smartphone(opposite the display 4042 at the frontside 4043) so that a healthparameter of a person can be monitored by bringing the backside of thesmartphone into contact with (or close proximity to) the skin of theperson that is to be monitored. In an embodiment, the antennas of thesensor system are at the surface of the smartphone so that the antennascan be brought into contact with the skin to improve radio wavetransmission. In other embodiments, the antennas are very near to thebackside external surface of the smartphone, e.g., within 0.25-3 mm. Forexample, the antennas may be covered by a thin layer of the materialthat forms the backside of the smartphone, e.g., a plastic materialhaving a thickness in the range of 0.25-3 mm thick. In an embodiment inwhich the backside is made of a metal (e.g., aluminum), there may beopenings in the aluminum at the locations of the antennas that are opento the antennas or filed with a material such as plastic through whichradio waves can more easily pass. The sensor system may include all ofthe components of the sensor system as described with reference to FIG.5 or only some of the components. For example, in an embodiment, thesensor system includes the RF front-end 548 and the digital basebandsystem 550 as shown in FIG. 5, but CPU functionality is provided by aCPU of the smartphone that performs many of the operations related tostandard smartphone functionality.

In another embodiment, multiple RF IC devices are included in a sensorsystem that is integrated into a smartphone. FIGS. 41A and 41B depict anembodiment of a smartphone 4100 that includes a sensor system 4110 withmultiple RF front-ends (e.g., in the form of multiple different RF ICdevices 4111 as described with reference to FIGS. 5-8D) integrated intothe smartphone. For example, as depicted in FIG. 41A, the RF IC devicesare configured in a two-dimensional array such that the sensor systemincludes in total, for example, 4×2=8 transmit antennas and 4×4=16receive antennas. In the embodiment depicted in FIG. 41B, the sensorsystem having multiple different RF IC devices is integrated into thesmartphone near the backside 4141 of the smartphone (opposite thedisplay 4142 at the frontside 4143) so that a health parameter of aperson can be monitored by bringing the backside of the smartphone intocontact with (or close proximity to) the skin of the person that is tobe monitored.

With an RF-based sensor system integrated into a smartphone, it ispossible to implement RF-based alignment similar to that described abovewith reference to FIGS. 36A-36E, 37A, and 37B. For example, it ispossible to generate digital alignment data from the RF-based sensorsystem and to use the digital alignment data to display a visualindicator of alignment in response to the digital alignment data. FIGS.42A and 42B depict an embodiment of a smartphone that includes a sensorsystem (not shown), for example, as described with reference to FIGS.5-8D that is configured to implement RF-based alignment of an antennaarray of the sensor system to a vein of a person that is to bemonitored. The alignment technique depicted in FIGS. 42A and 42Binvolves displaying an alignment feature (e.g., an alignment channel4224) and a graphical representation of a vein 4226 as described abovewith reference to FIGS. 36A-36E, 37A, and 37B. When the smartphone isused to monitor a health parameter of a person, the smartphone isbrought into contact with (or into close proximity to, e.g., less than10 mm, or more preferred less than 2 mm) the skin of the person to bemonitored and a graphical representation of a vein relative to analignment channel is displayed on the display of the smartphone toencourage a user of the smartphone to move and/or adjust the position ofthe smartphone relative to the vein to align the antenna array of thesensor system with the monitored vein. In an embodiment, the smartphoneis held in contact with the skin during health parameter monitoring toensure that the separation distance is constant throughout the healthmonitoring operation.

In an embodiment, a vein in the upper forearm is monitored to monitor ahealth parameter of a person. In such an embodiment, a vein in the upperforearm is monitored by placing the antenna array of the smartphone onthe forearm at the location of the vein that is intended to bemonitored. An indicator in the form of an alignment channel and agraphical representation of the vein are then displayed on the displayof the smartphone. Similar to the alignment technique described abovewith reference to FIGS. 36A-36E, FIG. 42A depicts a smartphone 4200 inwhich the graphical representation of the vein 4226 is out of alignmentwith the alignment feature 4224 and FIG. 42B depicts the smartphone inwhich the graphical representation of the vein is aligned with thealignment feature and in which an alignment message (e.g., “Aligned!”)is displayed.

As stated above, it may be desirable to monitor a vein in the forearm ofa person. FIG. 43A depicts an example of the veins in the arm 4350 of aperson. As shown in FIG. 43A, the veins include the cephalic vein 4351,the basilic vein 4352, the cephalic intermediate vein 4353, theintermediate vein of the elbow 4354, and the intermediate vein of theforearm 4355. FIG. 43B depicts a smartphone 4300, such as the smartphonedescribed with reference to FIGS. 41A-42B placed on the skin at thelocation of (or in close proximity to) a vein such as the intermediatevein of the forearm 4355. As illustrated in FIG. 43B, the backside ofthe smartphone is placed on the forearm (or in close proximity to theforearm) and the frontside of the smartphone, including the display, isvisible to a user of the smartphone. As shown in FIG. 43B, the alignmentchannel 4324 and the graphical representation of the vein 4326 areoriented to correspond to the orientation of the actual vein 4355 sothat the alignment indicator can be intuitively interpreted andmanipulated by the user. As described above, a person holding thesmartphone on the skin can move and/or adjust the position of thesmartphone relative to the vein as guided by the alignment channel andthe graphical representation of the vein to adjust the position of theantenna array of the sensor system to a desired position relative to thevein. In an embodiment, the user adjusts the lateral position of thesmartphone while holding the smartphone against the skin. Although anexample of an RF-based alignment indicator is described with referenceto FIG. 43B, other embodiments of an alignment indicator are possible.

As described above, in an embodiment, the alignment system of the healthmonitoring device is able to adapt the orientation of the displayedvisual indicator on the display of the device (e.g., the smartphone) tocorrespond to the orientation of the vein relative to health monitoringdevice. Thus, if the smartphone is held in a different orientationrelative to a vein, the displayed alignment features change accordingly.For example, with reference to FIG. 43B, the orientation of an alignmentchannel and a graphical representation of a vein may change to avertical orientation when the smartphone is rotated ninety degreesrelative to the vein.

In an embodiment, the sensor system, including the antenna array, may belocated in a different position within the smartphone to facilitatehealth monitoring. For example, in an embodiment, the sensor system,including the antenna array, is located at a point near the bottom ofthe smartphone. FIG. 44A depicts an example of the backside of asmartphone 4400 in which a sensor system 4410 including the antennaarray is located at a point near the bottom of the smartphone.Additionally, in this example, the sensor system is located off of thecenterline (e.g., to the left side) of the smartphone to, for example,avoid physically and/or electrically interfering with electronics thatmay be associated with a wired interface that is located at thecenterline of the smartphone. With reference to FIG. 44B, which depictsthe frontside of the smartphone 440, in an embodiment, the RF-basedalignment technique involves generating and displaying a graphicalindicator of alignment that graphically indicates to the user where toalign the smartphone with a vein that is intended to be monitored. Inthe example of FIG. 44B, the graphical indicator is an arrow 4428 thatis generated and displayed as a graphical element on the display of thesmartphone. As shown in FIG. 44B, the graphical alignment indicator iscollocated with the sensor system 4410 such that aligning the arrow withthe vein to be monitored also aligns the sensor system (e.g., theantenna array of the sensor system) with the vein to be monitored. In anembodiment, the graphical alignment indicator and the sensor system(e.g., the antenna array of the sensor system) are collocated whengraphical alignment indicator and the sensor system overlap with eachother or are within a few millimeters from each other when viewed from aplan view as shown in FIG. 44B. In an embodiment, an alignment featuresuch as the arrow 4428 can be used alone to achieve alignment. Inanother embodiment and as shown in FIG. 44B, an additional alignmentindicator may be provided to help achieve alignment between the sensorsystem and the monitored vein. As shown in FIG. 44B, the alignmentindicator includes an alignment channel 4424 and a graphicalrepresentation of the vein 4426 as described above. In an embodiment,multiple RF-based alignment features can be used together to achievealignment. Additionally, although an arrow is shown as an example of avisible alignment feature, other graphical elements on the graphicaluser interface, including lines, shapes, colors, and text can be used.

FIG. 44C illustrates a person holding the smartphone 4400 as describedwith reference to FIGS. 44A and 44B against the skin at the wrist 4430and using the alignment feature on the graphical user interface (e.g.,the arrow 4428 as shown in FIG. 44B) to align the sensor system of thesmartphone with the monitored vein 4435. FIG. 44C also shows anadditional alignment feature (e.g., an alignment channel 4424 and agraphical representation of the vein 4426) on the display device asshown in FIG. 44B to further help facilitate alignment between theantenna array of the sensor system and the monitored vein. In anembodiment, the alignment arrow helps the user to achieve coursealignment between the antenna array of the sensor system and themonitored vein and the alignment channel helps the user to achieve finealignment between the antenna array of the sensor system and themonitored vein. Also note that the alignment channel is oriented tomatch the orientation of the vein relative to the graphical userinterface of the smartphone in order to provide the user with anintuitive way to align the antenna array of the sensor system, which isembedded within the smartphone, with the monitored vein. For example,the orientation of the alignment channel matches the orientation of thevein in that the alignment channel, the graphical representation of thevein, and the actual vein run in parallel to each other (e.g., if notexactly in parallel, then roughly in parallel, e.g., to within aboutplus or minus 5 degrees).

In the embodiment of FIGS. 44A-44C, the alignment arrow 4428 isgenerated in response to RF signals generated by the sensor system 4410and is displayed on the display of the smartphone as a graphical elementof a graphical user interface. In another embodiment, a visual alignmentfeature is a visible marking on the body of the smartphone that is usedto align the sensor system of the smartphone with the vein that is to bemonitored. FIG. 45A depicts the backside of a smartphone 4500 in whichthe sensor system 4510 is located at a point near the bottom of thesmartphone, similar to the example described with reference to FIG. 44A.With reference to FIG. 45B, which depicts the frontside of thesmartphone 4500, an alignment feature 4556 is provided as a marking onthe body of the smartphone that is visible to a user of the smartphone.For example, the visible marking is a marking of a different color fromthe surrounding portion of the body or the visible marking is a grooveor bump in the body that is visible to a user of the smartphone. Othervisible markings on the body of the smartphone can also be used as avisual alignment indicator that can be seen by a user of the smartphone.In an embodiment, the alignment feature is referred to as a “physical”alignment feature because the alignment feature includes a physicalelement on the body of the smartphone (even if the physical element issimply a contrasting color or other visible marking). As shown in FIG.45B, the visible marking is collocated with the sensor system 4510 suchthat aligning the visible marking 4556 with the vein to be monitoredalso aligns the sensor system (e.g., the antenna array of the sensorsystem) with the vein to be monitored. In operation, a user of thesmartphone uses the visible marking to align the smartphone with a veinof a person as illustrated, for example, in FIG. 44C. In one embodiment,the visible alignment feature is the only alignment feature that existsfor aligning the sensor system to a monitored vein. In anotherembodiment, another alignment feature may be utilized in conjunctionwith the visible marking. For example, FIG. 45B depicts a physicalalignment feature on the body of the smartphone along with an alignmentchannel 4524 and a graphical representation of a vein 4426 displayed ona graphical user interface of the display.

In an embodiment, some components of the sensor system, such as thesensor system described with reference to FIGS. 5-7 are integrated intoa removable case for a smartphone and digital data generated by thesensor system (e.g., the digital baseband system 550 of FIG. 5) iscommunicated from the removable smartphone case to the smartphone via acommunications interface for further processing to determine a value ofa health parameter. FIG. 46 depicts a perspective view of an example ofa removable case 4660 for a smartphone (also referred to as a “removablesmartphone case,” a “smartphone case,” a “case,” or a “cover”). As shownin FIG. 46, the removable smartphone case includes a body having abackwall and a sidewall that goes around the perimeter of the backwall,which together form a bed within which a smartphone can be secured. Asis known in the field, the backwall typically includes an opening for acamera and the sidewall includes at least one opening that correspondsto buttons and/or interfaces on the side of the smartphone.

FIGS. 47A and 47B depict the backside and frontside, respectively, of anembodiment of a removable smartphone case 4760 that includes a sensorsystem 4710 having an RF front-end 4748, a processor 4750, acommunications interface 4762, and a battery 4764 integrated into thecase. In the example of FIGS. 47A and 47B, the RF front-end is similarto the RF front-end 548 described above with reference to FIG. 5 and theprocessor is similar to the digital baseband system 550 described withreference to FIG. 5. In the example of FIGS. 47A and 47B, thecommunications interface is a wireless interface, such as a BLUETOOTHlow energy (BLE) wireless interface although other wireless or wiredinterfaces are possible. The battery may be, for example, a lithium-ionrechargeable battery that has a thin profile and that is rechargeablevia wireless and or wired charging. FIG. 47C depicts a side cutaway viewof the removable smartphone case shown at cross section AA of FIG. 47A.As shown in FIG. 47C, the sensor system 4710 is integrated into the bodyof the case. In an embodiment, the antennas of the sensor system are atthe backside 4745 of the body of the removable smartphone case so thatthe antennas can be brought into contact with the skin to improve radiowave transmission. In other embodiments, the antennas are very near tothe backside external surface of the smartphone case, e.g., within0.25-3 mm. For example, the antennas may be covered by a thin layer ofthe material of the removable smartphone case, e.g., a plastic materialhaving a thickness in the range of 0.25-3 mm thick. In an embodiment,some or all of the components of the sensor system are embedded into thecase body and in other embodiments, some or all the components areattached to a surface of the case body. There are various ways in whichthe components of the sensor system can be connected to, attached to,and/or integrated with the case body. For example, the components of thesensor system may be embedded within a plastic material that is formedaround the components and that forms at least part of the case body. Inan embodiment, the antennas (e.g., the TX and RX antennas) are embeddedclose to the surface of the case body or at the surface of the case bodysuch that they are close to the surrounding environment and/or directlyexposed to the surrounding environment so that the antennas can bebrought into contact with (or into close proximity to) the skin of theperson that is to be monitored.

In the embodiment of FIGS. 47A-47C, the antennas of the RF front-end4748 are closely integrated with a semiconductor substrate of the RFfront-end (e.g., an RF IC) as is described, for example, with referenceto FIGS. 8A-8D. This may be particularly important at high frequencyranges such as the 122-126 GHz frequency range. However, in otherembodiments, the antennas (including the TX and/or RX antennas) may notbe so closely integrated with the semiconductor substrate of the RFfront-end. FIGS. 48A and 48B depict the frontside and backside,respectively, of an embodiment of a removable smartphone case 4860 thatincludes a sensor system 4810 in which an antenna array 4768 of the RFfront-end is separated from the semiconductor substrate 4769 (e.g., fromthe RF IC device) of the front RF front-end. For example, the antennasof the antenna array may be electrically connected by conductive paths4770 but physically separated from the RF IC device 4769 by 0.5-20centimeters. In an embodiment, the antennas of the sensor system are atthe surface of the body of the removable smartphone case so that theantennas can be brought into contact with the skin to improve radio wavetransmission. In other embodiments, the antennas are very near to thebackside external surface of the smartphone case, e.g., within 0.25-3mm.

In an embodiment, the communications interface of the sensor system maybe a wired communications interface. FIG. 49A depicts the backside of aremovable smartphone case 4960 in which the sensor system 4910 isintegrated into the case and the communications interface 4862 is awired interface such as a male interface that is configured to connectto a female interface of a smartphone. FIG. 49B depicts a perspectiveview of the removable smartphone case 4960 of FIG. 49A that depicts thecommunications interface 4862 through which information can becommunicated from the sensor system (e.g., an RF front-end and a digitalbaseband system) to a smartphone that is secured in the removablesmartphone case. In an embodiment, the removable smartphone case mayinclude additional components such as, for example, an alignmentindicator device (e.g., an LED or a speaker) or a display device thatcan be used for health monitoring including alignment of the healthmonitoring device with a vein of a person.

Whether the removable smartphone case includes a wireless communicationsinterface or a wired communications interface, the RF-based sensorsystem generates digital data in response to received radio waves. Thedigital data can be used for alignment of the sensor system and/or forhealth parameter monitoring. FIG. 50A illustrates alignment information(e.g., in the form of digital data generated by the sensor system 5010in response to received radio waves) being communicated from theremovable smartphone case 5060 to the smartphone 5000. In FIG. 50A,front views of the removable smartphone case and the smartphone areshown separate from each other to more clearly illustrate thecommunication of alignment information between the removable smartphonecase and the smartphone although it should be understood that duringnormal operation, the smartphone would be held within the removablesmartphone case and the communications interface of the smartphone casewould communicate with the corresponding communications interface of thesmartphone. As shown in FIG. 50A, the smartphone displays an RF-basedalignment channel 5024 and a graphical representation of a vein 5026 inresponse to the received alignment information.

FIG. 50B illustrates health parameter information (e.g., in the form ofdigital data generated by the sensor system in response to receive radiowaves) being communicated from the removable smartphone case 5060 to thesmartphone 5000. As shown in FIG. 50B, the smartphone displays a valueof a health parameter (e.g., a blood glucose level of 120 mg/dL) that isdetermined in response to the received health parameter information. Inan embodiment, some of the processing used to determine the value of thehealth parameter (e.g., the blood glucose level) is implemented by aprocessor of the smartphone (e.g., a processor such as the APPLE A13processor or the QUALCOMM Snapdragon processor). For example, theprocessor of the smartphone may be configured (e.g., through computerreadable instructions and/or through specialized special-purposehardware) to implement at least some portion of the machine learningengine, the health parameter determination engine, and/or the trainedmodel database as described above with reference to FIGS. 27-31. Inother embodiments, at least some portion of the machine learning engine,the health parameter determination engine, and/or the trained modeldatabase may be implemented in other processing devices such as aspecial-purpose processing device (e.g., a processing device of thesmartphone and/or a processing device of the smartphone case). Thecommunication of alignment information and/or health parameterinformation between a removable smartphone case and a smartphone mayinvolve wired or wireless (e.g., BLE) communications depending on theconfiguration of the smartphone and/or the smartphone case. The examplesof FIGS. 50A and 50B apply to both wired and wireless communicationsinterfaces.

Various techniques for aligning an antenna array of a sensor system withan object, such as a vein of a person to be monitored, have beendescribed above. Some of the techniques utilize digital data generatedfrom received RF signals and other techniques utilize a visual markingon a smartphone or on a removable smartphone case. Additional alignmenttechniques that utilize alignment features integrated into the body of adevice are described below. Such techniques utilize, for example,magnetic elements and/or out-of-plane physical features to promotealignment between an antenna array of a sensor system and an object,such as an alignment patch that is worn by the person to be monitored.

FIGS. 51A-51C depict an embodiment of a smartphone 5100 that includesmagnetic alignment features 5170 integrated into the body of thesmartphone. As is described below, the magnetic alignment features areconfigured to mate with alignment features of an alignment element(e.g., an alignment patch) that is worn by the person to be monitored.FIG. 51A is a view of the backside of a smartphone that includes asensor system 5110 (including an antenna array) integrated into thesmartphone and magnetic alignment elements 5170 integrated into the bodyof the smartphone. FIG. 51B depicts a view of the frontside of thesmartphone with the location of the sensor system 5110 shown althoughthe sensor system is not actually visible from the frontside of thesmartphone. FIG. 51C depicts a side cutaway view of the smartphone atcross section AA of FIG. 51A, which shows the sensor system 5110 and themagnetic alignment elements 5170 integrated into the device body. In anembodiment, the magnetic alignment features are magnets such as smallcylindrical neodymium magnets (e.g., 1-5 mm in diameter and 0.25-1 mmthick) that are secured into the case body. Although an exampleconfiguration of magnetic alignment elements is described with referenceto FIGS. 51A-51C, other configurations of magnetic alignment elementsare possible. Additionally, the sensor system and collocated alignmentfeatures could be located in other positions within the smartphone, suchas, for example, the positions described with reference to FIGS. 44A,44B, and 47A-47C.

In the example of FIGS. 51A-51C, the alignment features are integratedinto the body of a smartphone. In another embodiment, the alignmentfeatures are integrated into the body of a removable smartphone case.FIGS. 52A-52C depict an embodiment of a removable smartphone case 5260that includes magnetic alignment elements 5270 integrated into the bodyof the removable smartphone case. As is described below, the magneticalignment elements are configured to mate with alignment features of analignment element (e.g., an alignment patch) that is worn by the personto be monitored. FIG. 52A is a view of the backside of a removablesmartphone case that includes a sensor system 5210 (including an antennaarray) and magnetic alignment elements 5270 integrated into thesmartphone case. FIG. 52B depicts a view of the frontside of thesmartphone case with the location of the sensor system 5210 shownalthough the sensor system may not actually be visible from thefrontside of the smartphone case. FIG. 52C depicts a side cutaway viewof the smartphone case at cross section AA of FIG. 52A, which shows thesensor system 5210 and the magnetic alignment elements 5270 integratedinto the case body. In an embodiment, the magnetic alignment elementsare small cylindrical neodymium magnets (e.g., 1-5 mm in diameter and0.25-1 mm thick) that are secured into the case body. Although anexample configuration of magnetic alignment features is described withreference to FIGS. 52A-52C, other configurations of magnetic alignmentelements are possible. Additionally, the sensor system and collocatedalignment features could be located in other positions within theremovable smartphone case, such as, for example, the positions describedwith reference to FIGS. 44A, 44B, and 47A-47C.

As stated above, the magnetic alignment features of the smartphone orsmartphone case are configured to mate with alignment features of analignment element, such as alignment patch, that is to be worn by aperson. FIGS. 53A and 53B depict an embodiment of an alignment element5380 in the form of an alignment patch that includes magnetic alignmentfeatures 5382 configured to mate with alignment features of the healthmonitoring device (e.g., a smartphone and/or a removable smartphonecase). FIG. 53A is a top plan view of the alignment patch that includesfour magnetic alignment elements located around an opening 5383(referred to as an “alignment window”) in the alignment patch. In anembodiment, the alignment window is provided so that a person can alignthe alignment patch with a vein to be monitored during application ofthe patch to the skin. For example, a person moves the alignment patchrelative to the skin so that a targeted vein can be seen through thealignment window and then adheres the alignment patch to the skin suchthat the targeted vein is still visible through the alignment windowafter the alignment patch is adhered to the skin. In addition toproviding visibility for alignment of the patch to a targeted vein, thealignment window also provides a pathway for radio waves to travelbetween the antenna array and the targeted vein that is free ofinterference from the patch material. For example, transmitted radiowaves are able to pass from the transmit antenna(s) directly to the skinand targeted vein without passing through the patch material and atleast some of the reflected radio waves are able to pass from the veinto the receive antennas free of interference from the patch material.

FIG. 53B is a side cutaway view of the alignment patch 5380 alongsection AA of FIG. 53A, which depicts a multilayer patch structure thatincludes a base layer 5384, an adhesive layer 5385, and a top layer5386. In an embodiment, the base layer provides structural support forthe adhesive layer and for the top layer. The adhesive layer isconfigured to adhere to a person's skin and may be covered by aremovable cover material until the alignment patch is applied to theskin. The top layer may be configured to provide structural support forthe magnetic alignment elements. The top layer may also be configuredwith functional and/or cosmetic characteristics that may help thealignment patch to be durable, comfortable, and/or cosmeticallyappealing while being worn by a person for an extended period of time(e.g., multiple days and/or weeks). With reference to FIG. 53A, thealignment patch may have a width dimension in the range of, for example,1.27-7.62 cm and a height in the range of 1.27-7.62 cm, although otherdimensions are possible. With reference to FIG. 53B, the thickness ofthe alignment patch may vary from, for example, 0.5-10 mm, althoughother thicknesses are possible. Although an example structure of analignment patch is described with reference to FIGS. 53A and 53B, itshould be understood that the configuration of an alignment element suchas an alignment path can vary with for example, different materiallayers and different numbers, sizes, shapes, and orientations of thealignment features (e.g., the alignment magnets). For example, in theembodiment of FIGS. 53A and 53B, the alignment window is void of anypatch material. In other embodiments, the alignment window may include atransparent material and/or a material that passes radio waves with lessinterference than the patch material that forms the borders of thealignment window. In still other embodiments, the entire patch (or aportion thereof) may be transparent and the alignment window may beformed by visible markings, such as a visible square that defines thealignment window.

FIGS. 54A-54C illustrate an example alignment process between a healthmonitoring device (such as a smartphone or a smartphone and a removablesmartphone case) and an alignment element (such as an alignment patch)in which the health monitoring device and the alignment element includematching configurations of magnetic alignment features. FIG. 54A depictsan example of the alignment patch 5480 of FIG. 53A being worn on theskin 5401 of a person to be monitored. In the example of FIG. 54A, thealignment patch is attached to (e.g., adhered to) the skin at the rightwrist of the person with the alignment window 5483 aligned with a veinin the wrist such that the vein is located within and/or visible withinthe alignment window. FIG. 54B illustrates the health monitoring device5400 being moved towards the alignment patch 5380 that is worn on theskin of the person as shown in FIG. 54A. As illustrated, the magneticalignment elements of the health monitoring device are brought intoclose proximity to the corresponding magnetic alignment elements of thealignment patch. When the magnetic alignment elements 5470 of the healthmonitoring device and the magnetic alignment elements 5482 of thealignment patch get close enough to each other, magnetic attractionbetween the mutually aligned magnets will become strong enough that themagnetic alignment elements of the health monitoring device magneticallyattach to the magnetic alignment elements of the alignment patch. FIG.54C illustrates the magnetic alignment elements of the health monitoringdevice magnetically attached to the corresponding magnetic alignmentelements of the alignment patch. In the example of FIGS. 53A-54C, themagnetic attachment between the two sets of magnetic alignment elementscauses the antenna array of the sensor system (not shown in FIGS. 54Band 54C but located between the magnetic alignment elements) to bealigned with the alignment window of the alignment patch. In anembodiment, the antenna array of the sensor system is aligned with thealignment window of the alignment patch when the antenna array isdirectly over the alignment window. Assuming the alignment window of thealignment patch is aligned with a vein to be monitored, the antennaarray of the sensor system will also be aligned with the vein that is tobe monitored. For example, the antenna array of the sensor system willbe positioned directly over the vein that is to be monitored such thattransmitted and reflected radio waves can pass between the antenna arrayand the vein through the alignment window. In an embodiment, the antennaarray (including the transmit antenna(s) and the two-dimensional arrayof receive antennas) is aligned with the alignment window. In otherembodiments, only the transmit antennas are aligned with the alignmentwindow or only the two-dimensional array of receive antennas are alignedwith the alignment window. Thus, the alignment window can serve a dualpurpose of providing visibility for aligning the patch with a vein whilealso providing a low interference pathway through which radio waves canpass, e.g., a lower interference than a pathway that goes through thepatch material.

In an embodiment, the health monitoring device 5400 is kept in theposition as indicated in FIG. 54C while a health monitoring operation isconducted. For example, a health monitoring operation may take on theorder of seconds to complete or a health monitoring operation may takeon the order of a minute or a couple of minutes to complete. In theembodiment of FIGS. 54A-54C, the magnetic alignment elements 5470 and5482 of both the health monitoring device and the alignment patch aremagnetized to provide a strong magnetic attraction between the twosides. For example, as shown in FIG. 52A, the sensor system iscollocated with the four alignment features, from a plan viewperspective, a rectangle defined by the four alignment features overlapswith the position of the sensor system. However, in other embodiments,one side or the other may include magnetized alignment elements whilethe other side is simply a magnetic material. Although a particularconfiguration of alignment elements is described with reference to FIGS.51A-54C, other configurations, including other materials, numbers ofelements, sizes of elements, shapes of elements, orientations ofelements, etc. are possible.

In the examples described above, the alignment features of the healthmonitoring device are collocated with the sensor system. For example,the magnetic alignment elements are located around the perimeter of theantenna array of the sensor system. In an embodiment, alignment featuresare “collocated” with an antenna array of the sensor system when, from aplan view perspective, the area defined by a perimeter that is formed byconnecting the alignment features (or a line between alignment features)overlaps with at least a portion of the antenna array. However, in otherembodiments, the alignment features may not be collocated with theantenna array of the sensor system. FIGS. 55A and 55B depict an exampleof a removable smartphone case in which the antenna array of the sensorsystem is not collocated with the alignment features. In particular,FIGS. 55A and 55B depict backside and frontside views, respectively, ofa removable smartphone case 5560, similar to that described above withreference to FIGS. 52A-52C, in which the alignment features 5570 arelocated in an upper portion of the removable smartphone case while thesensor system 5510 (in this case including the antenna array) is locatedin a lower portion of the removable smart phone case. In such anembodiment, an alignment device that is worn on the skin of a person maybe configured to align with the magnetic alignment features on thehealth monitoring device while also aligning the antenna array of thesensor system with a vein to be monitored. Embodiments in which theantenna array is not collocated with the alignment features includeother health monitoring devices such as smartphones, smartwatches, etc.Additionally, embodiments in which the antenna array is not collocatedwith the alignment features may involve alignment features other thanmagnetic alignment features.

In the examples described above with reference to FIGS. 51A-55B, thealignment features integrated into the body of the health monitoringdevice are magnetic alignment features. In other embodiments, thealignment feature, or alignment features, may be physical elements suchas physical elements that are “out-of-plane” with a major plane of thedevice body. For example, out-of-plane alignment features may includephysical features such as bumps or grooves in the outer surface of thesmartphone body that are configured to promote alignment between thesmartphone and another device such as an alignment patch that includescorresponding physical alignment features. FIGS. 56A-56C depict anembodiment of a smartphone 5600 with out-of-plane physical elements 5690that are integrated into the device body and configured to promotealignment between an antenna array of a sensor system and an object suchas an alignment patch. As is described below, the out-of-plane alignmentfeatures are configured to mate with out-of-plane alignment features ofan alignment element (e.g., an alignment patch) that is worn by theperson to be monitored. FIG. 56A is a view of the backside of asmartphone that includes a sensor system 5610 (including an antennaarray) integrated into the smartphone and out-of-plane alignmentelements integrated into the body of the smartphone. FIG. 56B depicts aview of the frontside of the smartphone with the location of the sensorsystem 5610 shown although the sensor system is not actually visiblefrom the frontside of the smartphone. FIG. 56C depicts a side cutawayview of the smartphone at cross section AA of FIG. 56A, which shows thesensor system 5610 and the out-of-plane alignment elements integratedinto the backside 5641 of the device body. In particular, the sidecutaway view shows that the out-of-plane alignment elements 5690 areseen as grooves or channels that are formed by sidewalls and a bottomwall that are not in the same plane as a plane that includes the majorsurface of the backside (opposite the display 5642) of the smartphone.For example, the sidewalls and bottom wall of the grooves or channelsare not coplanar with the major plane of the device body. In theembodiment of FIGS. 56A-56C, the out-of-plane alignment features aregrooves, channels, or cutouts that are formed by portions of thesmartphone body that are not in the same plane as the major plane of thebackside surface of the smartphone body. Although an exampleconfiguration of out-of-plane alignment features is described withreference to FIGS. 56A-56C, other configurations of out-of-planealignment elements are possible. Additionally, other embodiments ofphysical alignment features may be used to ensure that an antenna arrayof an RF-based sensor system is aligned with an object such as analignment patch and/or a vein that is to be monitored.

In the example of FIGS. 56A-56C, the out-of-plane alignment features5690 are integrated into the body of a smartphone 5600. In anotherembodiment, the alignment features are integrated into the body of aremovable smartphone case. FIGS. 57A-57C depict an embodiment of theremovable smartphone case 5960 that includes out-of-plane alignmentelements 5790 integrated into the body of the removable smartphone case.As is described below, the out-of-plane alignment features areconfigured to mate with out-of-plane alignment features of an alignmentelement (e.g., an alignment patch) that is worn by the person to bemonitored. FIG. 57A is a view of the backside of a removable smartphonecase that includes a sensor system 5710 (including an antenna array) andout-of-plane alignment elements 5790 integrated into the smartphonecase. FIG. 57B depicts a view of the frontside of the smartphone casewith the location of the sensor system 5710 shown although the sensorsystem may not actually be visible from the frontside of the smartphonecase. FIG. 57C depicts a side cutaway view of the smartphone case atcross section AA of FIG. 57A, which shows the sensor system and theout-of-plane alignment elements 5790 integrated into the case body. Inan embodiment, the out-of-plane alignment features are grooves,channels, or cutouts that are formed into the case body as describedabove with reference to FIGS. 56A-56C. For example, the out-of-planefeatures are formed by portions of the smartphone body that are not inthe same plane as the major surface of the backside of the smartphonecase. Although an example configuration of out-of-plane alignmentfeatures is described with reference to FIGS. 57A-57C, otherconfigurations of out-of-plane alignment elements are possible.

As stated above, the out-of-plane alignment features are configured tomate with out-of-plane alignment features of an alignment element, suchas alignment patch, that is to be worn by a person to be monitored.FIGS. 58A and 58B depict an embodiment of an alignment patch 5880 thatincludes out-of-plane alignment features 5892 configured to mate without-of-plane alignment features 5890 of the health monitoring device(e.g., a smartphone 5600 and/or a removable smartphone case 5760). FIG.58A is a top plan view of the alignment patch that includes four raisedstructures 5892 located around an opening 5883 (referred to as an“alignment window”) in the alignment patch. FIG. 58B is a side cutawayview of the alignment patch along section AA of FIG. 58A, which depictsa multilayer patch structure that includes a base layer 5884, anadhesive layer 5885, a top layer 5886, and the raised structures 5892that are raised above and out-of-plane with a major surface of thealignment patch. For example, the alignment features are out-of-planewith a major surface 5893 of the top layer of the alignment patch. In anembodiment, the base layer provides structural support for the adhesivelayer and for the top layer. The adhesive layer is configured to adhereto a person's skin and may be covered by a removable cover materialuntil the alignment patch is applied to the skin. The top layer may beconfigured to provide structural support for the raised structures. Thetop layer may also be configured with functional and/or cosmeticcharacteristics that may help the alignment patch to be durable,comfortable, and/or cosmetically appealing while being worn by a personfor an extended period of time (e.g., multiple days and/or weeks). Withreference to FIG. 58A, the alignment patch may have a width dimension inthe range of, for example, 1.27-7.62 cm and a height in the range of1.27-7.62 cm although other dimensions are possible. With reference toFIG. 58B, the thickness of the alignment patch may vary from, forexample, 0.5-10 mm, although other thicknesses are possible. Although anexample structure of an alignment patch is described with reference toFIGS. 58A and 58B, it should be understood that the configuration of analignment element such as an alignment patch can vary with, for example,different material layers and different numbers, sizes, shapes, andorientations of the alignment features (e.g., the out-of-plane alignmentelements).

FIGS. 59A-59C illustrate an example alignment process between a healthmonitoring device 5900 (such as a smartphone or a smartphone held withina removable smartphone case) and an alignment element 5980 (such as analignment patch) in which the health monitoring device and the alignmentelement include matching or complimentary configurations of out-of-planealignment features. FIG. 59A depicts an example of the alignment patch5980 being worn on the skin of a person to be monitored. In the exampleof FIG. 59A, the alignment patch is attached (e.g., adhered to) the skinat the right wrist of a person with the alignment window 5983 alignedwith a vein in the wrist such that the vein is located within and/orvisible within the alignment window. FIG. 59B illustrates the healthmonitoring device 5900 being moved towards the alignment patch 5980 thatis worn on the skin 5901 of the person as shown in FIG. 59A. Asillustrated, the out-of-plane alignment elements 5990 of the healthmonitoring device are brought into close proximity to the correspondingout-of-plane alignment elements 5992 of the alignment patch 5980. Whenthe out-of-plane alignment elements of the health monitoring device andthe out-of-plane alignment elements of the alignment patch get closeenough to each other, they engage and mutually align with each other. Inparticular, in this example, the out-of-plane alignment features of thepatch, which include raised structures that extend above the major topplane of the patch, and the out-of-plane alignment features of thehealth monitoring device, which include grooves that extend below themajor backside surface of the health monitoring device, fit togethersuch that the raised structures fit snuggly within the grooves. When fitsnuggly together, the complimentary shapes of the raised structures andthe grooves reduce or eliminate lateral movement between the healthmonitoring device and the alignment patch, which in turn results in astable alignment between the antenna array of the sensor system and themonitored vein. FIG. 59C illustrates the out-of-plane alignment elements5990 of the health monitoring device seated on top of the out-of-planealignment features 5992 of the alignment patch. In the example of FIGS.59A-59C, engagement of the two sets of out-of-plane alignment elementscauses the antenna array of the sensor system (sensor system not shownin FIGS. 59B and 59C but positioned as shown in FIGS. 57A-57C) to bealigned with the alignment window of the alignment patch. In anembodiment, the antenna array of the sensor system is aligned with thealignment window of the alignment patch when the antenna array isdirectly over the alignment window. Assuming the alignment window of thealignment patch is aligned with a vein to be monitored (e.g., a portionof the vein is located within and/or visible within the alignmentwindow), the antenna array of the sensor system will also be alignedwith the vein that is to be monitored. For example, the antenna array ofthe sensor system will be positioned directly over the vein that is tobe monitored such that transmitted and reflected radio waves can passbetween the antenna array and the vein through the alignment window.Thus, the alignment window can serve a dual purpose of providingvisibility for aligning the patch with a vein while also providing a lowinterference pathway through which radio waves can pass, e.g., a lowerinterference than a pathway that goes through the patch material. In anembodiment, the antenna array (including the transmit antenna(s) and thetwo-dimensional array of receive antennas) is aligned with the alignmentwindow. In other embodiments, only the transmit antenna or antennas arealigned with the alignment window or only the two-dimensional array ofreceive antennas is aligned with the alignment window. In an embodiment,the health monitoring device is kept in the position as indicated inFIG. 59C while a health monitoring operation is conducted. For example,a health monitoring operation may take on the order of seconds tocomplete or a health monitoring operation may take on the order of aminute or a couple of minutes to complete.

In the examples described above, the alignment features are integratedinto the body of a smartphone and/or a removable smartphone case. Inother embodiments, alignment features may be integrated into healthmonitoring devices that have other form factors. FIGS. 60A and 60Bdepict perspective views of a health monitoring device 6000 in the formof a smartwatch in which alignment features such as magnetic alignmentelements 6070 are integrated into the backside of the smartwatch body.As shown in FIG. 60B, the magnetic alignment elements 6070 arecollocated with a sensor system 6010 (which in this example includes anantenna array) in that the magnetic alignment elements are locatedaround the perimeter of the antenna array. In an embodiment, themagnetic alignment elements are configured to mate with magneticalignment elements integrated into an alignment element, such as analignment patch, that is worn on the skin of a person. For example, analignment patch such as the alignment patch described above withreference to FIGS. 53A and 53B is worn on the wrist and a smartwatch isworn on the wrist and over the patch such that the magnetic alignmentelements of the smartwatch align with the magnetic alignment elements ofthe alignment patch. FIG. 60C is a side cutaway view of the smartwatch6000 from FIGS. 60A and 60B attached around a wrist 6030 with themagnetic alignment features 6070 of the smartwatch magnetically engagedwith complementary magnetic alignment features 6082 of an alignmentpatch 6080 that is attached to the skin of the wrist so that thealignment window 6083 is aligned with a vein.

In the example of FIGS. 60A-60C, the smartwatch includes alignmentfeatures in the form of magnetic alignment elements. In otherembodiments, a smartwatch may be configured with another type ofalignment feature, such as out-of-plane alignment features. FIGS. 61Aand 61B depict perspective views of a health monitoring device in theform of a smartwatch 6100 in which out-of-plane alignment features 6190are integrated into the backside of the smartwatch body. In theembodiment of FIG. 61B, the out-of-plane alignment features are channelsor grooves in the body of the smartwatch that extend below the majorsurface of the backside of the smartwatch body. Additionally, as shownin FIG. 61B, the out-of-plane alignment elements are collocated with asensor system 6110 (which in this example includes an antenna array) inthat the out-of-plane alignment elements are located around theperimeter of the antenna array. In an embodiment, the out-of-planealignment elements are configured to mate with out-of-plane alignmentelements integrated into an alignment element, such as an alignmentpatch, that is worn on the skin of a person as described above withreference to FIGS. 58A-59C. For example, an alignment patch as describedabove with reference to FIGS. 58A and 58B is worn on the wrist and asmartwatch is worn on the wrist and over the alignment patch such thatthe out-of-plane alignment elements of the smartwatch align with theout-of-plane alignment elements of the alignment patch. FIG. 61C is aside cutaway view of the smartwatch 6100 from FIG. 61B attached around awrist with the out-of-plane alignment features 6190 of the smartwatchseated on top of complementary out-of-plane alignment features 6192 ofan alignment patch 6180 that is attached to the skin of the wrist sothat the alignment window 6183 is aligned with a vein.

In another embodiment, a health monitoring system that includes anRF-based sensor system as described above may be integrated into adevice such as a watch strap or watch band. FIGS. 62A and 62B depict anembodiment in which an RF-based health monitoring system 6210 isintegrated into a watch strap 6290 and 6292. In the embodiment of FIGS.62A and 62B, the health monitoring system 6210 is integrated into afirst piece of 6290 of a two piece watch strap although the healthmonitoring system could be integrated into the second piece 6292.Alternatively, the watch strap may be a single piece. The particularconfiguration of the watch strap can vary depending on, for example,clasp design, whether there even is a clasp, single piece, multiplepiece, etc. In the example shown in FIG. 62A, the RF-based healthmonitoring system includes an RF-based sensor system 6248 such asdescribed above, a processor 6250, a communications interface 6262, anda battery 6264. In an embodiment, the elements are similar to elementsas described above with reference to FIGS. 47A-47C, in which similarelements are integrated into a removable smartphone case. In the exampleof FIGS. 62A and 62B, the watch case 6002 is a smartwatch that includesa compatible communications interface 6294, a processor 6296, and abattery 6298. In such an embodiment, the communications interface 6262in the watch strap can communicate digital data (which is generated, forexample, by the RF IC device 6248 in response to received radio waves)to the communications interface 6294 of the watch case 6002. In otherembodiments, the watch case may be a conventional watch (e.g., withmechanical watch movement pieces and without a wireless communicationsinterface, processor, or battery or a watch that does not include acommunications interface that is compatible with the communicationsinterface of the strap) and the communications interface 6262 of thewatch strap 6290 can communicate with another compatible device such asa nearby smartphone or other computing device such as a laptop ordesktop computer. In other embodiments, the communications interface6262 of the watch strap may be able to communicate with both an attachedsmartwatch case 6002 and a nearby computing device such as a smartphone.

FIG. 62B depicts a side cutaway view of the first piece of the watchstrap 6290 that shows the health monitoring system 6210 integratedwithin the watch strap. For example, the communications interface 6262,the processor 6250, and the RF IC device 6248 are fabricated onsemiconductor substrates and the battery 6264 has a thin profile, e.g.,0.5-5 mm. In the example of FIGS. 62A and 62B, an RF-based sensor systemis integrated into a watch strap. However, in other embodiments, theRF-based sensor system is integrated into a clasp or buckle for a watchstrap. In still another embodiment, strap described above with referenceto FIGS. 62A and 62B may be a strap that does not include the watchcase. For example, the strap shown in FIGS. 62A and 62B is a continuous,e.g., single piece, strap that does not include the watch case. In suchan embodiment, the communications interface in the strap can communicatewith another computing device such as a smartwatch, a smartphone, orsome other computing device. In an embodiment, alignment features may beintegrated into the strap similar to the alignment features describedabove with reference to FIGS. 51A-61C.

In another embodiment, the health monitoring device may be integratedinto a wearable health monitoring system that is continuously worn onthe body via, for example, an adhesive. FIGS. 63A-63F depict an exampleof wearable health monitoring system that includes a health monitoringdevice 6300 (FIGS. 63A and 63B) and an alignment element 6380 (FIGS. 63Cand 63D), such as an alignment patch. In use, the alignment element isattached to the skin on of a person and the health monitoring device isattached to the alignment element. FIG. 63A is a top view of a healthmonitoring device 6300 that includes an RF-based sensor system 6310(e.g., an RF IC device) that includes components similar to thosedescribed above with reference to FIGS. 47A-47C and FIGS. 5-8D. FIG. 63Bis a side view of the health monitoring device of FIG. 63A. In theexample of FIGS. 63A and 63B, the health monitoring device includes anRF front-end 6348 (e.g., embodied as an RF IC device), a processor 6350(e.g., including a digital baseband system), a communications interface6362, and battery 6364. The health monitoring device also includesattachment features 6371 that are configured to engage with attachmentfeatures of the alignment element 6380. FIGS. 63C and 63D depict a topview and side view, respectively, of the alignment element 6380 such asan alignment patch. With reference to FIG. 63C, the alignment patchincludes four attachment features 6373 spaced to correspond to theperimeter of the health monitoring device shown in FIGS. 63A and 63B.The attachment features 6371 of the health monitoring device 6300 andthe attachment features 6373 of the alignment patch 6380 are configuredto engage with each other when the health monitoring device is broughtinto contact with the alignment patch. In an embodiment, the attachmentfeatures include angled and flexible components (e.g., clip structures)that allow the heath monitoring device to be “snapped” into position onthe alignment patch and held securely. In an embodiment, the attachmentfeatures are also configured such that the health monitoring device canbe removed on demand by a user by applying force to the healthmonitoring device. Various attachment features including, structural,magnetic, and/or adhesive may be incorporated into the health monitoringdevice and the alignment patch so that the health monitoring device canbe securely attached to the alignment patch but also removed from thealignment patch when desired.

In an embodiment, an alignment window 6383 is provided within thealignment patch 6380 so that a person can align the alignment patch witha vein to be monitored during application of the patch to the skin. Forexample, a person moves the alignment patch relative to the skin so thata targeted vein can be seen through the alignment window and thenadheres the alignment patch to the skin such that the targeted vein isstill visible through the alignment window after the alignment patch isadhered to the skin. FIG. 63D is a side cutaway view of the alignmentpatch 6380 along section AA of FIG. 63C, which depicts a multilayerpatch structure that includes a base layer 6384, an adhesive layer 6385,and a top layer 6386. In an embodiment, the base layer providesstructural support for the adhesive layer and for the top layer. Theadhesive layer is configured to adhere to a person's skin and may becovered by a removable cover material (not shown) until the alignmentpatch is applied to the skin. The top layer may be configured to providestructural support for the attachment features 6373. The top layer mayalso be configured with functional and/or cosmetic characteristics thatmay help the alignment patch to be durable, comfortable, and/orcosmetically appealing while being worn by a person for an extendedperiod of time (e.g., multiple days and/or weeks). With reference toFIG. 63C, the alignment patch may have a width dimension in the rangeof, for example, 1-20 cm and a height in the range of 1-15 cm, althoughother dimensions are possible. With reference to FIG. 63D, the thicknessof the alignment patch may vary from, for example, 0.5-10 mm, althoughother thicknesses are possible. Although an example structure of analignment patch 6380 is described with reference to FIGS. 63C and 63D,it should be understood that the configuration of an alignment elementsuch as an alignment path can vary with for example, different materiallayers and different numbers, sizes, shapes, and orientations of theattachment features. For example, in the embodiment of FIGS. 63C and63D, the alignment window is void of any patch material. In otherembodiments, the alignment window 6383 may include a transparentmaterial. In still other embodiments, the entire patch (or a portionthereof) may be transparent and the alignment window may be formed byvisible markings, such as a visible square that defines the alignmentwindow. In the embodiment of FIGS. 63C and 63D, the alignment window ispositioned to correspond to the location of the RF IC device (e.g.,aligned with the antenna array) so that radio waves can pass between theskin of the person and the antenna array unimpeded by material of thealignment patch. That is, the wearable health monitoring system isconfigured so that the location of the alignment window 6383 matches thelocation of the antenna array of the RF-based sensor system (e.g., withthe RF IC device 6348) when the health monitoring device is attached tothe alignment patch. When the health monitoring device is attached tothe alignment patch, the RF-based sensor system is directly above thealignment window. FIG. 63E is a top view of the health monitoring systemthat depicts the health monitoring device 6300 attached to the alignmentelement 6380 via the alignment features of both the health monitoringdevice and the alignment element 6371 and 6373, respectively. FIG. 63Fdepicts a side view of the wearable health monitoring system describedwith reference to FIGS. 63A-63E attached to the skin 6301 of a person.In the example of FIGS. 63A-63F, the attachment features 6373 of thehealth monitoring device 6300 and the attachment features 6373 of thealignment patch 6380 serve a dual purpose in that they enable attachmentbetween the health monitoring device and the alignment patch and theycause the antenna array of the sensor system to be aligned with thealignment window 6383 of the alignment patch. Assuming the alignmentwindow of the alignment patch is aligned with a vein to be monitored,the antenna array of the sensor system will also be aligned with thevein that is to be monitored. In an embodiment, the wearable healthmonitoring system is worn on the skin as indicated in FIG. 63F for anextended period of time, e.g., days or weeks, and health monitoring isperformed on a continuous or periodic basis. In an embodiment, aparticular health monitoring operation may take on the order of secondsto complete or a health monitoring operation may take on the order of aminute or a couple of minutes to complete. In an embodiment, thecommunications interface 6362 of the health monitoring system isconfigured to wirelessly communicate (e.g., via BLE) digital datagenerated from the RF-based health monitoring to a nearby computingdevice such as a smartphone or smartwatch.

In another embodiment, a health monitoring system that includes anRF-based sensor system as described above may be integrated into adevice such as a ring 6400 that is to be worn on a finger or toe. FIGS.64A-64C depict an embodiment in which an RF-based health monitoringsystem 6410 is integrated into a ring that is to be worn on a finger ortoe. In particular, FIG. 64A is a side view, FIG. 64B is front view, andFIG. 64C is a perspective view of the ring. In the example shown inFIGS. 64A and 64B, the RF-based health monitoring system 6410 includesan RF front-end 6448 such as described above (e.g., an RF IC device), aprocessor 6450, a communications interface 6462, and a battery 6464. Inan embodiment, the elements are similar to elements as described abovewith reference to FIGS. 47A-47C and FIGS. 8A-8D. In the example of FIGS.64A-64C, the communications interface 6462 is compatible with acomputing device such as a smartwatch, a smartphone, or a desktop orlaptop computer. In an embodiment, the antenna array of the RF front-endis located close to the inner surface 6411 of the ring so that theantenna array is close to the skin of the finger or toe on which thering is worn. FIG. 64C depicts the RF front-end 6448 of the sensorsystem at the inner surface 6411 of the ring 6400.

FIG. 65 is an example computing system 6500 that includes an RF-basedsensor system 6548, a processor 6550, memory 6551, a communicationsinterface 6562, a battery 6564, a display device 6542, a tactileindicator device 6543, and a speaker 6545. The computing device may beembodied as any of the devices described herein, including, for example,a smartwatch, a smartphone, a removable smartphone case, a strap for awatch, a ring, or another health monitoring device. The computing devicemay include all of the components or some portion of the components. Inan embodiment, the tactile indicator device may include a mechanism thatgenerates tactile feedback (e.g., a vibration) in response to electricalcontrol signal. The RF-based sensor system may comprise an RF-basedsensor system as described herein, e.g., as described with reference toFIGS. 5-8D. The processor, memory, communications interface, battery,display device and speaker may be elements as are known in the field.

Although the operations of the method(s) herein are shown and describedin a particular order, the order of the operations of each method may bealtered so that certain operations may be performed in an inverse orderor so that certain operations may be performed, at least in part,concurrently with other operations. In another embodiment, instructionsor sub-operations of distinct operations may be implemented in anintermittent and/or alternating manner.

It should also be noted that at least some of the operations for themethods described herein may be implemented using software instructionsstored on a computer useable storage medium for execution by a computer.As an example, an embodiment of a computer program product includes acomputer useable storage medium to store a computer readable program.

The computer-useable or computer-readable storage medium can be anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system (or apparatus or device). Examples ofnon-transitory computer-useable and computer-readable storage mediainclude a semiconductor or solid state memory, magnetic tape, aremovable computer diskette, a random access memory (RAM), a read-onlymemory (ROM), a rigid magnetic disk, and an optical disk. Currentexamples of optical disks include a compact disk with read only memory(CD-ROM), a compact disk with read/write (CD-R/W), and a digital videodisk (DVD).

Alternatively, embodiments of the invention may be implemented entirelyin hardware or in an implementation containing both hardware andsoftware elements. In embodiments which use software, the software mayinclude but is not limited to firmware, resident software, microcode,etc.

Although specific embodiments of the invention have been described andillustrated, the invention is not to be limited to the specific forms orarrangements of parts so described and illustrated. The scope of theinvention is to be defined by the claims appended hereto and theirequivalents.

What is claimed is:
 1. A method for operating a health parametermonitoring system, the method comprising: transmitting radio waves belowthe skin surface of a person; receiving radio waves on a two-dimensionalarray of receive antennas of an antenna array, the received radio wavesincluding a reflected portion of the transmitted radio waves;determining an alignment of the antenna array relative to a vein in theperson in response to the received radio waves; and outputting a signalthat is indicative of the determined alignment of the antenna arrayrelative to the vein.
 2. The method of claim 1, wherein the signalcomprises a visual indicator of alignment.
 3. The method of claim 1,further comprising displaying a visual indicator of alignment on adisplay of a health parameter monitoring system in response to thesignal.
 4. The method of claim 3, wherein the visual indicator ofalignment includes an alignment feature and a graphical representationof a detected vein.
 5. The method of claim 2, wherein the visualindicator of alignment includes an alignment feature on a display of ahealth parameter monitoring system.
 6. The method of claim 1, whereinthe visual indicator of alignment includes an alignment feature that isstationary on a display and a graphical representation of a detectedvein that moves in response to movement of the antenna array relative tothe detected vein.
 7. The method of claim 1, wherein the visualindicator of alignment includes an alignment channel that is stationaryon a display and a graphical representation of a detected vein thatmoves in response to movement of the antenna array relative to thedetected vein.
 8. The method of claim 7, wherein the alignment channeland the graphical representation of the vein are oriented parallel tothe vein.
 9. The method of claim 1, wherein the visual indicator ofalignment includes an alignment feature and a graphical representationof a detected vein.
 10. The method of claim 1, further comprisingemitting light from a light source of a health parameter monitoringsystem in response to the output signal, wherein the light is indicativeof alignment of the antenna array relative to the vein.
 11. The methodof claim 1, further comprising generating an audio signal that isindicative of alignment of the antenna array relative to the vein inresponse to the output signal.
 12. The method of claim 1, furthercomprising generating a tactile signal that is indicative of alignmentof the antenna array relative to the vein in response to the outputsignal.
 13. The method of claim 1, further comprising displaying avisual indicator of alignment of the antenna array relative to the veinon a display of a smartwatch in response to the output signal.
 14. Themethod of claim 1, further comprising displaying an alignment channeland a graphical representation of a vein as a visual indicator ofalignment of the antenna array relative to the vein on a display of asmartphone in response to the output signal.
 15. The method of claim 1,further comprising generating a visual indicator of alignment of theantenna array relative to the vein in response to the output signal whenit is determined that the antenna array is aligned with the vein. 16.The method of claim 15, wherein the antenna array is aligned with thevein when an equal number of receive antennas are on either side of thevein.
 17. The method of claim 1, further comprising generating anaudible indicator of alignment in response to the output signal when itis determined that the antenna array is aligned with the vein.
 18. Themethod of claim 1, further comprising generating a tactile indicator ofalignment in response to the output signal when it is determined thatthe antenna array is aligned with the vein.
 19. The method of claim 1,wherein the transmitting and receiving are implemented by a integratedcircuit device that is integrated into a removable smartphone case andwherein the determining and outputting are implemented by a processor ofa smartphone that is connected to the removable smartphone case.
 20. Themethod of claim 19, further comprising displaying a visual indicator ofalignment on a display of the smartphone in response to the outputsignal.
 21. The method of claim 1, wherein the transmitting, thereceiving, the determining, and the outputting are implemented bycircuits integrated into a removable smartphone case.
 22. The method ofclaim 21, further comprising generating a visual indicator of alignmenton the removable smartphone case in response to the output signal.